{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Martin_Replication_Log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}17 Feb 2019, 12:28:06

{com}. do "/var/folders/nq/tt38hq7j0fnb95dyrqk463p00000gn/T//SD34569.000000"
{txt}
{com}. /* 
>  THIS .DO FILE DOES THE FOLLOWING:
>  
>  1. Section 1 imports the raw data, cleans data, and creates new variables for analysis. 
>         It then save a file for analysis where the unit of observation is the respondent
>  
>  2. Section 2 reshapes the data so that each observation is a single conjoint profile within a
>         profile pair, and saves the resulting dataset.
>         
>  3. Section 3 produces the tables and figures presented in the main paper
>  
>  4. Section 4 produces the tables and figures presented in Online Appendix A
>  
>  5. Section 5 produces the tables and figures presented in Online Appendix C
>  
>  */
. 
. clear all
{txt}
{com}. set more off
{txt}
{com}. set scheme s1mono
{txt}
{com}. 
. * PLEASE SET YOUR FILEPATH HERE: 
. 
.         cd "/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"
{res}/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files
{txt}
{com}.                 
. 
. ************************************************************************************
. 
. **************          SECTION 1: DATA CLEANING AND VARAIBLE CREATION          
. 
. ************************************************************************************
. 
. // Import raw data file
.         use "Conjoint_experiment_raw.dta"
{txt}
{com}.         
. // Fix mixlabed observations (i.e. on day X enumerator recorded doing survey 2 twice): 
.         * Had 5 pairs: were able to use paper records to fix 3, are dropping other 2
. 
.                 * 3 mislabeled surveys: wrong day. Decided which were correct based on town selected.
.                         replace dayenumeration=7 if dayenumeration==6 & town=="Kyotera"
{txt}(1 real change made)

{com}.                         replace dayenumeration=3 if dayenumeration==5 & town=="Seeta"
{txt}(1 real change made)

{com}.                         replace dayenumeration=4 if dayenumeration==3 & town=="Jinja town"
{txt}(1 real change made)

{com}.                 
.                 * Drop 2 observations where paper records don't help determine correct survey date / enumerator
.                         drop if enumerator==1 & dayenumeration==8 & interviewnumber==8 & age==45
{txt}(1 observation deleted)

{com}.                         drop if enumerator==1 & dayenumeration ==10 & interviewnumber==7 & age==37
{txt}(1 observation deleted)

{com}. 
. // Fix District & Location Variables
.         
.         * West Team wrote Masaka instead of Rakai on day 7 because option wasn't on drop-down
.                 replace area="Rakai" if area=="Masaka" & dayenum==7
{txt}(46 real changes made)

{com}. 
.         * Fix enumerator errors in entering District - corrected using paper records
.                 replace area="Iganga" if area=="Jinja" & dayenum==8
{txt}(1 real change made)

{com}.                 replace area="Lwengo" if area=="Masaka" & dayenum==9
{txt}(1 real change made)

{com}.                 
. 
.         * Fix enumerator errors in selecting town of enumeration (done using paper records)
.                 * Create dummy for each enumeration team
.                 gen team=.
{txt}(778 missing values generated)

{com}.                         replace team=1  if enumerator==5 | enumerator==4 | enumerator==1 | enumerator==3 | enumerator==10
{txt}(389 real changes made)

{com}.                         replace team=2  if enumerator==8 | enumerator==2 | enumerator==9 | enumerator==7 | enumerator==6
{txt}(389 real changes made)

{com}.                 
.                 * Label raw town variables
.                 label var town "Town according to Enum entry: uncorrected"
{txt}
{com}.                 
.                 * Create corrected town variable
.                 gen town_2=""
{txt}(778 missing values generated)

{com}.                         label var town_2 "Correct town according to Paper records"
{txt}
{com}.                         
.                         replace town_2="Kalagi" if dayenum==3 & team==1
{txt}town_2 was {res}str1{txt} now {res}str6
{txt}(24 real changes made)

{com}.                         replace town_2="Jinja Town" if dayenum==4 & team==1
{txt}town_2 was {res}str6{txt} now {res}str10
{txt}(45 real changes made)

{com}.                         replace town_2="Bugembe" if dayenum==5 & team==1
{txt}(48 real changes made)

{com}.                         replace town_2="Mafubira" if dayenum==6 & team==1
{txt}(43 real changes made)

{com}.                         replace town_2="Masese" if dayenum==7 & team==1
{txt}(50 real changes made)

{com}.                         replace town_2="Iganga Town" if dayenum==8 & team==1
{txt}town_2 was {res}str10{txt} now {res}str11
{txt}(45 real changes made)

{com}.                         replace town_2="Nakalama" if dayenum==9 & team==1
{txt}(45 real changes made)

{com}.                         replace town_2="Njeru" if dayenum==10 & team==1
{txt}(44 real changes made)

{com}.                         replace town_2="Wakitaka" if dayenum==11 & team==1
{txt}(45 real changes made)

{com}.                         
.                         replace town_2="Seeta" if dayenum==3 & team==2
{txt}(36 real changes made)

{com}.                         replace town_2="Masaka Town" if dayenum==4 & team==2
{txt}(38 real changes made)

{com}.                         replace town_2="Lukaya Town" if dayenum==5 & team==2
{txt}(46 real changes made)

{com}.                         replace town_2="Nyendo" if dayenum==6 & team==2
{txt}(43 real changes made)

{com}.                         replace town_2="Kyotera" if dayenum==7 & team==2
{txt}(46 real changes made)

{com}.                         replace town_2="Saza" if dayenum==8 & team==2
{txt}(44 real changes made)

{com}.                         replace town_2="Kinoni" if dayenum==9 & team==2
{txt}(46 real changes made)

{com}.                         replace town_2="Kalisizo" if dayenum==10 & team==2
{txt}(45 real changes made)

{com}.                         replace town_2="Kabaale Bugonzi" if dayenum==11 & team==2
{txt}town_2 was {res}str11{txt} now {res}str15
{txt}(45 real changes made)

{com}.                                         
.                 * Fix incorrect area names using paper records
.                 replace area="Buikwe" if town_2=="Njeru"
{txt}(44 real changes made)

{com}.                 replace area="Rakai" if town_2=="Kalisizo"
{txt}(45 real changes made)

{com}.                                                                                                                                                 
. // Create additional variables used in heterogeneity analysis
.                 * Days a week worked: combine data from each occupational group
.                         gen days_week=.
{txt}(778 missing values generated)

{com}.                                 replace days_week=medays_wk if market==1
{txt}(257 real changes made)

{com}.                                 replace days_week=bddays_week if boda==1
{txt}(254 real changes made)

{com}.                                 replace days_week=sedays_week if shop==1
{txt}(267 real changes made)

{com}.                                 label var days_week "Reported days a week at work"
{txt}
{com}.                 * Weekly income
.                         gen weekly_profit=days_week*daily_income
{txt}
{com}.                         label var weekly_profit "Estimated weekly profits"
{txt}
{com}.         
.                 * Education: create dummies for highest education level = post-secondary 
.                         gen postsec_ed=cond(years_ed>=14,1,0) if years_ed!=.
{txt}
{com}.                         
.                 * Clarify label on voting question 
.                         label var presvote "1 if voted in last presidential election"
{txt}
{com}. 
. // Construct unique PID: this is done by concatenating the day of enumeration; the enumerator ID number;
.         * and what number interview the respondent was for that enumerator-day
.         * Ex: enumerator 10, enumeration day 1, 6th survey of day --> pid=100106
.         
.                 tostring dayenum, gen(daystr)
{txt}daystr generated as {res:str2}

{com}.                 tostring interviewnumber, gen(idstr)
{txt}idstr generated as {res:str2}

{com}.                 tostring enumerator, gen(enumstr)
{txt}enumstr generated as {res:str2}

{com}.         
.                 foreach x of numlist 1/9 {c -(}
{txt}  2{com}.                         qui replace daystr="0`x'" if daystr=="`x'"
{txt}  3{com}.                         qui replace idstr="0`x'" if idstr=="`x'"
{txt}  4{com}.                         qui replace enumstr="0`x'" if enumstr=="`x'"
{txt}  5{com}.                         {c )-}
{txt}
{com}.                 
.                 egen pid=concat(enumstr daystr idstr)
{txt}
{com}.                 destring pid, replace
{txt}pid has all characters numeric; {res}replaced {txt}as {res}long
{txt}
{com}.                 move pid enumerator
{txt}
{com}.                 
. // Create enumerator & Town Fixed Effects
.                 * Create enumerator dummy variables:
.                         tab enumerator, gen(e_)

 {txt}Enumerator {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
   1. Agnes {c |}{res}         88       11.31       11.31
{txt}     2. Ben {c |}{res}         57        7.33       18.64
{txt}   3. Betty {c |}{res}         88       11.31       29.95
{txt}    4. Dean {c |}{res}         54        6.94       36.89
{txt}  5. Esther {c |}{res}         71        9.13       46.02
{txt}   6. Gonza {c |}{res}         87       11.18       57.20
{txt}  7. Joseph {c |}{res}         87       11.18       68.38
{txt} 8. Justine {c |}{res}         72        9.25       77.63
{txt}  9. Rogers {c |}{res}         86       11.05       88.69
{txt} 10. Stuart {c |}{res}         88       11.31      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        778      100.00
{txt}
{com}.                 * Create town-level dummy variables
.                         tab town_2, gen(townfe_)

   {txt}Correct town {c |}
   according to {c |}
  Paper records {c |}      Freq.     Percent        Cum.
{hline 16}{c +}{hline 35}
        Bugembe {c |}{res}         48        6.17        6.17
{txt}    Iganga Town {c |}{res}         45        5.78       11.95
{txt}     Jinja Town {c |}{res}         45        5.78       17.74
{txt}Kabaale Bugonzi {c |}{res}         45        5.78       23.52
{txt}         Kalagi {c |}{res}         24        3.08       26.61
{txt}       Kalisizo {c |}{res}         45        5.78       32.39
{txt}         Kinoni {c |}{res}         46        5.91       38.30
{txt}        Kyotera {c |}{res}         46        5.91       44.22
{txt}    Lukaya Town {c |}{res}         46        5.91       50.13
{txt}       Mafubira {c |}{res}         43        5.53       55.66
{txt}    Masaka Town {c |}{res}         38        4.88       60.54
{txt}         Masese {c |}{res}         50        6.43       66.97
{txt}       Nakalama {c |}{res}         45        5.78       72.75
{txt}          Njeru {c |}{res}         44        5.66       78.41
{txt}         Nyendo {c |}{res}         43        5.53       83.93
{txt}           Saza {c |}{res}         44        5.66       89.59
{txt}          Seeta {c |}{res}         36        4.63       94.22
{txt}       Wakitaka {c |}{res}         45        5.78      100.00
{txt}{hline 16}{c +}{hline 35}
          Total {c |}{res}        778      100.00
{txt}
{com}.                 
.                 
. // Create variables needed to compare average conjoint ranking to hypothetical willingness to act (Appendix C4)
.         * Clean goprotest variable
.                 replace goprotest=. if goprotest==-99
{txt}(1 real change made, 1 to missing)

{com}.         * Generate average ranking in conjoint experiment across all 8 profiles 
.         egen avg_rank=rowmean(rank1_* rank2_*)
{txt}
{com}.                 label var avg_rank "Average severity ranking in conjoint"
{txt}
{com}.         * Generate average likelihood of taking action in post-treatment vignette (for Table 9)
.         egen avg_action=rowmean(goprotest contact_official campaign_against talkneighb)
{txt}
{com}.                 label var avg_action "Average likelihood of political action in response to scandal"
{txt}
{com}.                         
. // Save data file where unit of observation is each respondent
.         save "respondent_level_clean.dta", replace
{txt}file respondent_level_clean.dta saved

{com}. 
.         
.         
. *******************************************************************************************
. *******************************************************************************************
. 
. ********        SECTION 2: PREPARE AND RESHAPE DATA FOR CONJOINT ANALYSIS               
. 
. *******************************************************************************************
. *******************************************************************************************
. 
. // PART 1: CREATE DUMMIES FOR TREATMENT ASSIGNMENT FOR EACH ATTRIBUTE IN EACH PROFILE 
.         // AND GENERATE OUTCOME VARIABLES FOR EACH PROFILE WITHIN EACH PAIR
.         * a and b refer to whether a profile appeared first or second. 1-4 indicate profile pair number.
.         * So, "_a1" indicates a variable reports the treatment assignment for the first profile in pair 1
. 
. // ATTRIBUTE 1: ELECTED VS. APPOINTED OFFICIALS
.         
.         gen ATTRIBUTE_1=.
{txt}(778 missing values generated)

{com}.         label var ATTRIBUTE_1 "-----------------------"
{txt}
{com}.         
.         gen elect_a1=cond(rdn>.5,1,0) 
{txt}
{com}.         gen elect_b1=cond(rdn2>.5,1,0) 
{txt}
{com}.         gen elect_a2=cond(rdn3>.5,1,0) 
{txt}
{com}.         gen elect_b2=cond(rdn4>.5,1,0) 
{txt}
{com}.         gen elect_a3=cond(rdn5>.5,1,0) 
{txt}
{com}.         gen elect_b3=cond(rdn6>.5,1,0) 
{txt}
{com}.         gen elect_a4=cond(rdn7>.5,1,0) 
{txt}
{com}.         gen elect_b4=cond(rdn8>.5,1,0) 
{txt}
{com}.                 
.         gen appt_a1=cond(rdn<=.5,1,0)
{txt}
{com}.         gen appt_b1=cond(rdn2<=.5,1,0)
{txt}
{com}.         gen appt_a2=cond(rdn3<=.5,1,0)
{txt}
{com}.         gen appt_b2=cond(rdn4<=.5,1,0)
{txt}
{com}.         gen appt_a3=cond(rdn5<=.5,1,0)
{txt}
{com}.         gen appt_b3=cond(rdn6<=.5,1,0)
{txt}
{com}.         gen appt_a4=cond(rdn7<=.5,1,0)
{txt}
{com}.         gen appt_b4=cond(rdn8<=.5,1,0)
{txt}
{com}.         
. 
. // ATTRIBUTE 2: CENTRAL VS. LOCAL GOVERNMENT
. 
.         gen ATTRIBUTE_2=.
{txt}(778 missing values generated)

{com}.         label var ATTRIBUTE_2 "-----------------------" 
{txt}
{com}.                 
.         gen central_a1=cond(rd2n>.5,1,0)
{txt}
{com}.         gen central_b1=cond(rd2n2>.5,1,0)
{txt}
{com}.         gen central_a2=cond(rd2n3>.5,1,0)
{txt}
{com}.         gen central_b2=cond(rd2n4>.5,1,0)
{txt}
{com}.         gen central_a3=cond(rd2n5>.5,1,0)       
{txt}
{com}.         gen central_b3=cond(rd2n6>.5,1,0)
{txt}
{com}.         gen central_a4=cond(rd2n7>.5,1,0)
{txt}
{com}.         gen central_b4=cond(rd2n8>.5,1,0)
{txt}
{com}. 
.         gen local_a1=cond(rd2n<=.5,1,0)
{txt}
{com}.         gen local_b1=cond(rd2n2<=.5,1,0)
{txt}
{com}.         gen local_a2=cond(rd2n3<=.5,1,0)
{txt}
{com}.         gen local_b2=cond(rd2n4<=.5,1,0)                
{txt}
{com}.         gen local_a3=cond(rd2n5<=.5,1,0)
{txt}
{com}.         gen local_b3=cond(rd2n6<=.5,1,0)
{txt}
{com}.         gen local_a4=cond(rd2n7<=.5,1,0)
{txt}
{com}.         gen local_b4=cond(rd2n8<=.5,1,0)
{txt}
{com}. 
. // ATTRIBUTE 3: DONOR, TAX, OR TRANSFER FUNDS
.         
.         gen ATTRIBUTE_3=.
{txt}(778 missing values generated)

{com}.         label var ATTRIBUTE_3 "-----------------------"
{txt}
{com}.         
.         gen donor_a1=cond(rd3n<(1/3),1,0)
{txt}
{com}.         gen donor_b1=cond(rd3n2<(1/3),1,0)
{txt}
{com}.         gen donor_a2=cond(rd3n3<(1/3),1,0)      
{txt}
{com}.         gen donor_b2=cond(rd3n4<(1/3),1,0)
{txt}
{com}.         gen donor_a3=cond(rd3n5<(1/3),1,0)
{txt}
{com}.         gen donor_b3=cond(rd3n6<(1/3),1,0)
{txt}
{com}.         gen donor_a4=cond(rd3n7<(1/3),1,0)      
{txt}
{com}.         gen donor_b4=cond(rd3n8<(1/3),1,0)
{txt}
{com}.                 
.         gen tax_a1=cond(rd3n>=(1/3) & rd3n<(2/3),1,0)
{txt}
{com}.         gen tax_b1=cond(rd3n2>=(1/3) & rd3n2<(2/3),1,0)
{txt}
{com}.         gen tax_a2=cond(rd3n3>=(1/3) & rd3n3<(2/3),1,0)
{txt}
{com}.         gen tax_b2=cond(rd3n4>=(1/3) & rd3n4<(2/3),1,0)
{txt}
{com}.         gen tax_a3=cond(rd3n5>=(1/3) & rd3n5<(2/3),1,0)
{txt}
{com}.         gen tax_b3=cond(rd3n6>=(1/3) & rd3n6<(2/3),1,0)
{txt}
{com}.         gen tax_a4=cond(rd3n7>=(1/3) & rd3n7<(2/3),1,0)
{txt}
{com}.         gen tax_b4=cond(rd3n8>=(1/3) & rd3n8<(2/3),1,0)
{txt}
{com}.         
.         gen transfer_a1=cond(rd3n>(2/3),1,0)
{txt}
{com}.         gen transfer_b1=cond(rd3n2>(2/3),1,0)
{txt}
{com}.         gen transfer_a2=cond(rd3n3>(2/3),1,0)
{txt}
{com}.         gen transfer_b2=cond(rd3n4>(2/3),1,0)
{txt}
{com}.         gen transfer_a3=cond(rd3n5>(2/3),1,0)
{txt}
{com}.         gen transfer_b3=cond(rd3n6>(2/3),1,0)
{txt}
{com}.         gen transfer_a4=cond(rd3n7>(2/3),1,0)
{txt}
{com}.         gen transfer_b4=cond(rd3n8>(2/3),1,0)
{txt}
{com}. 
. // ATTRIBUTE 4: GAVE MONEY TO SELF, KIN/VILLAGE, OR ELECTION SUPPORT    
. 
. gen ATTRIBUTE_4=.
{txt}(778 missing values generated)

{com}.         label var ATTRIBUTE_4 "-----------------------"
{txt}
{com}.         
.         gen self_a1=cond(rd4n<(1/3),1,0)
{txt}
{com}.         gen self_b1=cond(rd4n2<(1/3),1,0)
{txt}
{com}.         gen self_a2=cond(rd4n3<(1/3),1,0)       
{txt}
{com}.         gen self_b2=cond(rd4n4<(1/3),1,0)
{txt}
{com}.         gen self_a3=cond(rd4n5<(1/3),1,0)
{txt}
{com}.         gen self_b3=cond(rd4n6<(1/3),1,0)       
{txt}
{com}.         gen self_a4=cond(rd4n7<(1/3),1,0)
{txt}
{com}.         gen self_b4=cond(rd4n8<(1/3),1,0)
{txt}
{com}. 
.         gen kinvill_a1=cond(rd4n>=(1/3) & rd4n<(2/3),1,0)
{txt}
{com}.         gen kinvill_b1=cond(rd4n2>=(1/3) & rd4n2<(2/3),1,0)
{txt}
{com}.         gen kinvill_a2=cond(rd4n3>=(1/3) & rd4n3<(2/3),1,0)
{txt}
{com}.         gen kinvill_b2=cond(rd4n4>=(1/3) & rd4n4<(2/3),1,0)
{txt}
{com}.         gen kinvill_a3=cond(rd4n5>=(1/3) & rd4n5<(2/3),1,0)
{txt}
{com}.         gen kinvill_b3=cond(rd4n6>=(1/3) & rd4n6<(2/3),1,0)
{txt}
{com}.         gen kinvill_a4=cond(rd4n7>=(1/3) & rd4n7<(2/3),1,0)
{txt}
{com}.         gen kinvill_b4=cond(rd4n8>=(1/3) & rd4n8<(2/3),1,0)
{txt}
{com}.                 
.         gen buyel_a1=cond(rd4n>(2/3),1,0)
{txt}
{com}.         gen buyel_b1=cond(rd4n2>(2/3),1,0)
{txt}
{com}.         gen buyel_a2=cond(rd4n3>(2/3),1,0)      
{txt}
{com}.         gen buyel_b2=cond(rd4n4>(2/3),1,0)
{txt}
{com}.         gen buyel_a3=cond(rd4n5>(2/3),1,0)
{txt}
{com}.         gen buyel_b3=cond(rd4n6>(2/3),1,0)      
{txt}
{com}.         gen buyel_a4=cond(rd4n7>(2/3),1,0)
{txt}
{com}.         gen buyel_b4=cond(rd4n8>(2/3),1,0)      
{txt}
{com}. 
. // ATTRIBUTE 5: STOLE FROM GOVERNMENT SALARIES, WATER, EDUCATION, INFRASTRUCTURE, OR HEALTH
. 
.         gen ATTRIBUTE_5=.
{txt}(778 missing values generated)

{com}.         label var ATTRIBUTE_5 "-----------------------"
{txt}
{com}.         
.         gen sal_a1=cond(rd5n<.2,1,0)
{txt}
{com}.         gen sal_b1=cond(rd5n2<.2,1,0)
{txt}
{com}.         gen sal_a2=cond(rd5n3<.2,1,0)
{txt}
{com}.         gen sal_b2=cond(rd5n4<.2,1,0)
{txt}
{com}.         gen sal_a3=cond(rd5n5<.2,1,0)
{txt}
{com}.         gen sal_b3=cond(rd5n6<.2,1,0)           
{txt}
{com}.         gen sal_a4=cond(rd5n7<.2,1,0)
{txt}
{com}.         gen sal_b4=cond(rd5n8<.2,1,0)
{txt}
{com}. 
.         gen water_a1=cond(rd5n>=.2 & rd5n<.4,1,0)
{txt}
{com}.         gen water_b1=cond(rd5n2>=.2 & rd5n2<.4,1,0)
{txt}
{com}.         gen water_a2=cond(rd5n3>=.2 & rd5n3<.4,1,0)
{txt}
{com}.         gen water_b2=cond(rd5n4>=.2 & rd5n4<.4,1,0)
{txt}
{com}.         gen water_a3=cond(rd5n5>=.2 & rd5n5<.4,1,0)
{txt}
{com}.         gen water_b3=cond(rd5n6>=.2 & rd5n6<.4,1,0)             
{txt}
{com}.         gen water_a4=cond(rd5n7>=.2 & rd5n7<.4,1,0)
{txt}
{com}.         gen water_b4=cond(rd5n8>=.2 & rd5n8<.4,1,0)
{txt}
{com}. 
.         gen educ_a1=cond(rd5n>=.4 & rd5n<.6,1,0)
{txt}
{com}.         gen educ_b1=cond(rd5n2>=.4 & rd5n2<.6,1,0)
{txt}
{com}.         gen educ_a2=cond(rd5n3>=.4 & rd5n3<.6,1,0)
{txt}
{com}.         gen educ_b2=cond(rd5n4>=.4 & rd5n4<.6,1,0)
{txt}
{com}.         gen educ_a3=cond(rd5n5>=.4 & rd5n5<.6,1,0)
{txt}
{com}.         gen educ_b3=cond(rd5n6>=.4 & rd5n6<.6,1,0)
{txt}
{com}.         gen educ_a4=cond(rd5n7>=.4 & rd5n7<.6,1,0)
{txt}
{com}.         gen educ_b4=cond(rd5n8>=.4 & rd5n8<.6,1,0)
{txt}
{com}. 
.         gen infra_a1=cond(rd5n>=.6 & rd5n<.8,1,0)
{txt}
{com}.         gen infra_b1=cond(rd5n2>=.6 & rd5n2<.8,1,0)      
{txt}
{com}.         gen infra_a2=cond(rd5n3>=.6 & rd5n3<.8,1,0)
{txt}
{com}.         gen infra_b2=cond(rd5n4>=.6 & rd5n4<.8,1,0)
{txt}
{com}.         gen infra_a3=cond(rd5n5>=.6 & rd5n5<.8,1,0)
{txt}
{com}.         gen infra_b3=cond(rd5n6>=.6 & rd5n6<.8,1,0)
{txt}
{com}.         gen infra_a4=cond(rd5n7>=.6 & rd5n7<.8,1,0)
{txt}
{com}.         gen infra_b4=cond(rd5n8>=.6 & rd5n8<.8,1,0)
{txt}
{com}. 
.         gen health_a1=cond(rd5n>=.8,1,0)
{txt}
{com}.         gen health_b1=cond(rd5n2>=.8,1,0)       
{txt}
{com}.         gen health_a2=cond(rd5n3>=.8,1,0)
{txt}
{com}.         gen health_b2=cond(rd5n4>=.8,1,0)       
{txt}
{com}.         gen health_a3=cond(rd5n5>=.8,1,0)
{txt}
{com}.         gen health_b3=cond(rd5n6>=.8,1,0)       
{txt}
{com}.         gen health_a4=cond(rd5n7>=.8,1,0)
{txt}
{com}.         gen health_b4=cond(rd5n8>=.8,1,0)       
{txt}
{com}. 
. // GENERATE VARIABLES REPRESENTING OUTCOMES IN EACH PROFILE IN EACH PAIR
. 
. // Generate  choice variables
.         gen choice_a1=cond(choice_1==1,1,0)
{txt}
{com}.         gen choice_b1=cond(choice_1==2,1,0)
{txt}
{com}.         
.         gen choice_a2=cond(choice_2==1,1,0)
{txt}
{com}.         gen choice_b2=cond(choice_2==2,1,0)
{txt}
{com}.         
.         gen choice_a3=cond(choice_3==1,1,0)
{txt}
{com}.         gen choice_b3=cond(choice_3==2,1,0)
{txt}
{com}.         
.         gen choice_a4=cond(choice_4==1,1,0)
{txt}
{com}.         gen choice_b4=cond(choice_4==2,1,0)
{txt}
{com}.         
.         gen rank_a1=rank1_1
{txt}
{com}.         gen rank_a2=rank1_2
{txt}
{com}.         gen rank_a3=rank1_3
{txt}
{com}.         gen rank_a4=rank1_4
{txt}
{com}.         
.         gen rank_b1=rank2_1
{txt}
{com}.         gen rank_b2=rank2_2
{txt}
{com}.         gen rank_b3=rank2_3
{txt}
{com}.         gen rank_b4=rank2_4     
{txt}
{com}. 
. 
. ********                        RESHAPE DATA FOR CONJOINT ANALYSIS                                      ********        
. 
. * Reshape data so that each observation is a single profile pair (4 observations per respondent) 
. reshape long choice_a elect_a appt_a central_a local_a donor_a tax_a transfer_a  self_a kinvill_a buyel_a sal_a water_a educ_a infra_a health_a ///
> choice_b elect_b appt_b central_b local_b donor_b tax_b transfer_b  self_b kinvill_b buyel_b sal_b water_b educ_b infra_b health_b rank_a rank_b, i(pid) j(profile)
{txt}(note: j = 1 2 3 4)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}     778   {txt}->{res}    3112
{txt}Number of variables            {res}     447   {txt}->{res}     346
{txt}j variable (4 values)                     ->   {res}profile
{txt}xij variables:
      {res}choice_a1 choice_a2 ... choice_a4   {txt}->   {res}choice_a
         elect_a1 elect_a2 ... elect_a4   {txt}->   {res}elect_a
            appt_a1 appt_a2 ... appt_a4   {txt}->   {res}appt_a
   central_a1 central_a2 ... central_a4   {txt}->   {res}central_a
         local_a1 local_a2 ... local_a4   {txt}->   {res}local_a
         donor_a1 donor_a2 ... donor_a4   {txt}->   {res}donor_a
               tax_a1 tax_a2 ... tax_a4   {txt}->   {res}tax_a
transfer_a1 transfer_a2 ... transfer_a4   {txt}->   {res}transfer_a
            self_a1 self_a2 ... self_a4   {txt}->   {res}self_a
   kinvill_a1 kinvill_a2 ... kinvill_a4   {txt}->   {res}kinvill_a
         buyel_a1 buyel_a2 ... buyel_a4   {txt}->   {res}buyel_a
               sal_a1 sal_a2 ... sal_a4   {txt}->   {res}sal_a
         water_a1 water_a2 ... water_a4   {txt}->   {res}water_a
            educ_a1 educ_a2 ... educ_a4   {txt}->   {res}educ_a
         infra_a1 infra_a2 ... infra_a4   {txt}->   {res}infra_a
      health_a1 health_a2 ... health_a4   {txt}->   {res}health_a
      choice_b1 choice_b2 ... choice_b4   {txt}->   {res}choice_b
         elect_b1 elect_b2 ... elect_b4   {txt}->   {res}elect_b
            appt_b1 appt_b2 ... appt_b4   {txt}->   {res}appt_b
   central_b1 central_b2 ... central_b4   {txt}->   {res}central_b
         local_b1 local_b2 ... local_b4   {txt}->   {res}local_b
         donor_b1 donor_b2 ... donor_b4   {txt}->   {res}donor_b
               tax_b1 tax_b2 ... tax_b4   {txt}->   {res}tax_b
transfer_b1 transfer_b2 ... transfer_b4   {txt}->   {res}transfer_b
            self_b1 self_b2 ... self_b4   {txt}->   {res}self_b
   kinvill_b1 kinvill_b2 ... kinvill_b4   {txt}->   {res}kinvill_b
         buyel_b1 buyel_b2 ... buyel_b4   {txt}->   {res}buyel_b
               sal_b1 sal_b2 ... sal_b4   {txt}->   {res}sal_b
         water_b1 water_b2 ... water_b4   {txt}->   {res}water_b
            educ_b1 educ_b2 ... educ_b4   {txt}->   {res}educ_b
         infra_b1 infra_b2 ... infra_b4   {txt}->   {res}infra_b
      health_b1 health_b2 ... health_b4   {txt}->   {res}health_b
            rank_a1 rank_a2 ... rank_a4   {txt}->   {res}rank_a
            rank_b1 rank_b2 ... rank_b4   {txt}->   {res}rank_b
{txt}{hline 77}

{com}. 
.         // Make new unique ID for each respondent-profile-pair (profile-pid)
.                         tostring pid, gen(pidstr)
{txt}pidstr generated as {res:str6}

{com}.                         tostring profile, gen(profstr)
{txt}profstr generated as {res:str1}

{com}.                         gen pid_prof=pidstr+profstr
{txt}
{com}.                         destring pid_prof, replace
{txt}pid_prof has all characters numeric; {res}replaced {txt}as {res}long
{txt}
{com}. 
. 
.         // Rename suffixes for next reshape
.                 rename choice_a chosen1
{res}{txt}
{com}.                 rename choice_b chosen2
{res}{txt}
{com}.                 local stems "elect appt central local donor tax transfer self kinvill buyel sal water educ infra health rank"
{txt}
{com}.                 foreach x of local stems {c -(}
{txt}  2{com}.                         rename `x'_a `x'1
{txt}  3{com}.                         rename `x'_b `x'2
{txt}  4{com}.                         {c )-}
{res}{txt}
{com}. 
.         // Reshape dataset so that each observation is a single profile (8 observations per respondent) 
.                 reshape long chosen elect appt central local donor tax transfer self kinvill buyel sal water educ infra health rank, i(pid_prof) j(profileab)
{txt}(note: j = 1 2)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}    3112   {txt}->{res}    6224
{txt}Number of variables            {res}     349   {txt}->{res}     333
{txt}j variable (2 values)                     ->   {res}profileab
{txt}xij variables:
                        {res}chosen1 chosen2   {txt}->   {res}chosen
                          elect1 elect2   {txt}->   {res}elect
                            appt1 appt2   {txt}->   {res}appt
                      central1 central2   {txt}->   {res}central
                          local1 local2   {txt}->   {res}local
                          donor1 donor2   {txt}->   {res}donor
                              tax1 tax2   {txt}->   {res}tax
                    transfer1 transfer2   {txt}->   {res}transfer
                            self1 self2   {txt}->   {res}self
                      kinvill1 kinvill2   {txt}->   {res}kinvill
                          buyel1 buyel2   {txt}->   {res}buyel
                              sal1 sal2   {txt}->   {res}sal
                          water1 water2   {txt}->   {res}water
                            educ1 educ2   {txt}->   {res}educ
                          infra1 infra2   {txt}->   {res}infra
                        health1 health2   {txt}->   {res}health
                            rank1 rank2   {txt}->   {res}rank
{txt}{hline 77}

{com}. 
.                 
.         //  Label variables for analysis
.                 label var elect "Elected"
{txt}
{com}.                 label var appt "Appointed"
{txt}
{com}.                 label var central "Central"
{txt}
{com}.                 label var local "Local"
{txt}
{com}.                 label var donor "Foreign aid"
{txt}
{com}.                 label var tax "Taxes"
{txt}
{com}.                 label var transfer "Central Transfers"
{txt}
{com}.                 label var self "On Himself"
{txt}
{com}.                 label var kinvill "Patronage"
{txt}
{com}.                 label var buyel "Clientelism"
{txt}
{com}.                 label var sal "Government Salaries"
{txt}
{com}.                 label var water "Water"
{txt}
{com}.                 label var educ "Education"
{txt}
{com}.                 label var infra "Infrastructure"
{txt}
{com}.                 label var health "Health Care"
{txt}
{com}.                 
.                 
.         // For analysis, make categorical variables for each conjoint attribute
.                 gen att1_s=""
{txt}(6224 missing values generated)

{com}.                         replace att1_s="Elected" if elect==1
{txt}att1_s was {res}str1{txt} now {res}str7
{txt}(3141 real changes made)

{com}.                         replace att1_s="Appointed" if appt==1
{txt}att1_s was {res}str7{txt} now {res}str9
{txt}(3083 real changes made)

{com}. 
.                 gen att2_s=""
{txt}(6224 missing values generated)

{com}.                         replace att2_s="Central" if central==1
{txt}att2_s was {res}str1{txt} now {res}str7
{txt}(3148 real changes made)

{com}.                         replace att2_s="Local" if local==1
{txt}(3076 real changes made)

{com}.                         
.                 gen att2=.
{txt}(6224 missing values generated)

{com}.                         replace att2=1 if local==1
{txt}(3076 real changes made)

{com}.                         replace att2=2 if central==1
{txt}(3148 real changes made)

{com}.                         label define att2 1 "Local" 2 "Central"
{txt}
{com}.                         label values att2 att2
{txt}
{com}. 
.                 gen att3_s=""
{txt}(6224 missing values generated)

{com}.                         replace att3_s="Foreign Aid" if donor==1
{txt}att3_s was {res}str1{txt} now {res}str11
{txt}(2136 real changes made)

{com}.                         replace att3_s="Tax" if tax==1
{txt}(2064 real changes made)

{com}.                         replace att3_s="Transfers" if transfer==1
{txt}(2024 real changes made)

{com}.                 
.                 gen att4=.
{txt}(6224 missing values generated)

{com}.                         replace att4=3  if kinvill==1
{txt}(2063 real changes made)

{com}.                         replace att4=2  if buyel==1
{txt}(2122 real changes made)

{com}.                         replace att4=1  if self==1
{txt}(2039 real changes made)

{com}.                         label define att4 1 "Himself" 2 "Clientelism" 3 "Patronage"
{txt}
{com}.                         label values att4 att4
{txt}
{com}.                         
.                 gen att5=.
{txt}(6224 missing values generated)

{com}.                         replace att5=1 if sal   ==1
{txt}(1319 real changes made)

{com}.                         replace att5=2 if water ==1
{txt}(1152 real changes made)

{com}.                         replace att5=3 if infra ==1
{txt}(1276 real changes made)

{com}.                         replace att5=4 if educ  ==1
{txt}(1244 real changes made)

{com}.                         replace att5=5 if health==1
{txt}(1233 real changes made)

{com}.                         label define att5 1 "Salaries" 2 "Water" 3 "Infrastructure/Roads" 4 "Education" 5 "Health Care"
{txt}
{com}.                         label values att5 att5
{txt}
{com}.                 
.         
.                 foreach x of numlist 1 3 {c -(}
{txt}  2{com}.                         encode att`x'_s, gen(att`x')
{txt}  3{com}.                         drop att`x'_s
{txt}  4{com}.                         {c )-}
{txt}
{com}.                 
.         // Create interactions for fully saturated model
.                 foreach x of varlist local tax transfer kinvill buyel water health educ infra {c -(}
{txt}  2{com}.                         gen elect_`x'=elect*`x'
{txt}  3{com}.                         {c )-}
{txt}
{com}.                 foreach x of varlist tax transfer kinvill buyel water health educ infra {c -(}
{txt}  2{com}.                         gen local_`x'=local*`x'
{txt}  3{com}.                         {c )-}
{txt}
{com}.                 foreach x of varlist kinvill buyel water health educ infra {c -(}
{txt}  2{com}.                         gen tax_`x'=tax*`x'
{txt}  3{com}.                         gen transfer_`x'=transfer*`x'
{txt}  4{com}.                         {c )-}
{txt}
{com}.                 foreach x of varlist water health educ infra {c -(}
{txt}  2{com}.                         gen kinvill_`x'=kinvill*`x'
{txt}  3{com}.                         gen buyel_`x'=buyel*`x'
{txt}  4{com}.                         {c )-}
{txt}
{com}.                 
.                 global interacts "elect_* local_* tax_* transfer_* kinvill_* buyel_*"
{txt}
{com}. 
. 
.         // Save data file where unit of observation is each profile (8 obs per respondent)
.                 save "profile_level_clean.dta", replace
{txt}file profile_level_clean.dta saved

{com}. 
.                 
.                 
. *******************************************************************************
. *******************************************************************************
. 
. ******** SECTION 3: ANALYSIS FOR MAIN PAPER                                             
. 
. *******************************************************************************
. *******************************************************************************
. 
. // Open profile-level dataset
.         use "profile_level_clean.dta", clear
{txt}
{com}. 
. 
. // Set globals for analysis: enumerator fixed effects and town fixed effects
.                 gl fe "e_* "
{txt}
{com}.                 gl townfe "townfe_*"
{txt}
{com}. 
.         
. // FIGURE 1: Main conjoint analysis
. 
.         // LEFT HAND SIDE: Change in Pr(official selected)
.         reg chosen i.att1 i.att2 i.att3 i.att5 i.att4 $fe $townfe, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    6224
                                                       {txt}F( 35,   777) ={res}   21.88
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0955
                                                       {txt}Root MSE      = {res} .47692

{txt}{ralign 87:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0984798{col 35}{space 2} .0137821{col 46}{space 1}    7.15{col 55}{space 3}0.000{col 63}{space 4} .0714252{col 76}{space 3} .1255344
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0160388{col 35}{space 2} .0125061{col 46}{space 1}    1.28{col 55}{space 3}0.200{col 63}{space 4}-.0085109{col 76}{space 3} .0405886
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2075561{col 35}{space 2} .0162839{col 46}{space 1}   12.75{col 55}{space 3}0.000{col 63}{space 4} .1755904{col 76}{space 3} .2395218
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2}  .031053{col 35}{space 2} .0159791{col 46}{space 1}    1.94{col 55}{space 3}0.052{col 63}{space 4}-.0003143{col 76}{space 3} .0624204
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0839465{col 35}{space 2}  .020741{col 46}{space 1}    4.05{col 55}{space 3}0.000{col 63}{space 4} .0432314{col 76}{space 3} .1246616
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0877868{col 35}{space 2} .0200665{col 46}{space 1}    4.37{col 55}{space 3}0.000{col 63}{space 4} .0483958{col 76}{space 3} .1271777
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1332131{col 35}{space 2} .0198371{col 46}{space 1}    6.72{col 55}{space 3}0.000{col 63}{space 4} .0942724{col 76}{space 3} .1721538
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2}  .246891{col 35}{space 2} .0202698{col 46}{space 1}   12.18{col 55}{space 3}0.000{col 63}{space 4} .2071009{col 76}{space 3} .2866811
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1443896{col 35}{space 2} .0157071{col 46}{space 1}   -9.19{col 55}{space 3}0.000{col 63}{space 4} -.175223{col 76}{space 3}-.1135561
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1969429{col 35}{space 2} .0154319{col 46}{space 1}  -12.76{col 55}{space 3}0.000{col 63}{space 4}-.2272361{col 76}{space 3}-.1666496
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0065627{col 35}{space 2} .0082336{col 46}{space 1}   -0.80{col 55}{space 3}0.426{col 63}{space 4}-.0227254{col 76}{space 3}    .0096
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0058086{col 35}{space 2} .0149456{col 46}{space 1}   -0.39{col 55}{space 3}0.698{col 63}{space 4}-.0351471{col 76}{space 3} .0235299
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0168185{col 35}{space 2} .0084306{col 46}{space 1}   -1.99{col 55}{space 3}0.046{col 63}{space 4}-.0333679{col 76}{space 3}-.0002691
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}  .004749{col 35}{space 2} .0101046{col 46}{space 1}    0.47{col 55}{space 3}0.639{col 63}{space 4}-.0150867{col 76}{space 3} .0245846
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0036219{col 35}{space 2} .0084907{col 46}{space 1}    0.43{col 55}{space 3}0.670{col 63}{space 4}-.0130455{col 76}{space 3} .0202893
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0125358{col 35}{space 2} .0141347{col 46}{space 1}   -0.89{col 55}{space 3}0.375{col 63}{space 4}-.0402824{col 76}{space 3} .0152109
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0109814{col 35}{space 2} .0145688{col 46}{space 1}   -0.75{col 55}{space 3}0.451{col 63}{space 4}-.0395802{col 76}{space 3} .0176175
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0123127{col 35}{space 2} .0147222{col 46}{space 1}   -0.84{col 55}{space 3}0.403{col 63}{space 4}-.0412126{col 76}{space 3} .0165872
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0047708{col 35}{space 2} .0147383{col 46}{space 1}   -0.32{col 55}{space 3}0.746{col 63}{space 4}-.0337024{col 76}{space 3} .0241608
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2} -.021012{col 35}{space 2} .0119971{col 46}{space 1}   -1.75{col 55}{space 3}0.080{col 63}{space 4}-.0445626{col 76}{space 3} .0025385
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0046348{col 35}{space 2}  .012231{col 46}{space 1}    0.38{col 55}{space 3}0.705{col 63}{space 4}-.0193749{col 76}{space 3} .0286445
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0161627{col 35}{space 2} .0110363{col 46}{space 1}   -1.46{col 55}{space 3}0.143{col 63}{space 4}-.0378273{col 76}{space 3} .0055018
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0073052{col 35}{space 2} .0120671{col 46}{space 1}    0.61{col 55}{space 3}0.545{col 63}{space 4}-.0163828{col 76}{space 3} .0309933
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0182892{col 35}{space 2} .0141876{col 46}{space 1}   -1.29{col 55}{space 3}0.198{col 63}{space 4}-.0461397{col 76}{space 3} .0095614
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}  -.00784{col 35}{space 2} .0125712{col 46}{space 1}   -0.62{col 55}{space 3}0.533{col 63}{space 4}-.0325175{col 76}{space 3} .0168376
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0037167{col 35}{space 2} .0121873{col 46}{space 1}   -0.30{col 55}{space 3}0.760{col 63}{space 4}-.0276406{col 76}{space 3} .0202071
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0101607{col 35}{space 2} .0122657{col 46}{space 1}    0.83{col 55}{space 3}0.408{col 63}{space 4} -.013917{col 76}{space 3} .0342385
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0002553{col 35}{space 2} .0130245{col 46}{space 1}    0.02{col 55}{space 3}0.984{col 63}{space 4}-.0253121{col 76}{space 3} .0258226
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0096857{col 35}{space 2} .0112095{col 46}{space 1}   -0.86{col 55}{space 3}0.388{col 63}{space 4}-.0316902{col 76}{space 3} .0123187
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}  .006833{col 35}{space 2} .0137347{col 46}{space 1}    0.50{col 55}{space 3}0.619{col 63}{space 4}-.0201284{col 76}{space 3} .0337945
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0089462{col 35}{space 2} .0121211{col 46}{space 1}   -0.74{col 55}{space 3}0.461{col 63}{space 4}-.0327402{col 76}{space 3} .0148479
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0017141{col 35}{space 2}   .01208{col 46}{space 1}   -0.14{col 55}{space 3}0.887{col 63}{space 4}-.0254274{col 76}{space 3} .0219992
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0013155{col 35}{space 2} .0111055{col 46}{space 1}   -0.12{col 55}{space 3}0.906{col 63}{space 4}-.0231157{col 76}{space 3} .0204848
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0066509{col 35}{space 2} .0124681{col 46}{space 1}   -0.53{col 55}{space 3}0.594{col 63}{space 4}-.0311261{col 76}{space 3} .0178242
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0044407{col 35}{space 2} .0127292{col 46}{space 1}    0.35{col 55}{space 3}0.727{col 63}{space 4}-.0205471{col 76}{space 3} .0294285
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3786323{col 35}{space 2} .0231763{col 46}{space 1}   16.34{col 55}{space 3}0.000{col 63}{space 4} .3331367{col 76}{space 3} .4241279
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_res
{txt}
{com}.         coefplot chosen_res, mcolor(black) ciopts(lcolor(black) lwidth(thin)) xlabel(-.1(.1).3) drop(_cons e_* $townfe) omitted base xline(0) headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Punished)") ytitle("") xsize(5) ysize(7) scale(.6)
{res}{txt}
{com}.         graph export "Tables/chosen.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/chosen.pdf written in PDF format)

{com}. 
.         // RIGHT-HAND SIDE: Change in 5-point severity ranking.         
.         reg rank i.att1 i.att2 i.att3 i.att5 i.att4 $fe $townfe, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    6224
                                                       {txt}F( 35,   777) ={res}   45.48
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1956
                                                       {txt}Root MSE      = {res} .81032

{txt}{ralign 87:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                 rank{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1288491{col 35}{space 2} .0227404{col 46}{space 1}    5.67{col 55}{space 3}0.000{col 63}{space 4} .0842092{col 76}{space 3}  .173489
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0133003{col 35}{space 2} .0210879{col 46}{space 1}    0.63{col 55}{space 3}0.528{col 63}{space 4}-.0280958{col 76}{space 3} .0546963
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .3010142{col 35}{space 2} .0285257{col 46}{space 1}   10.55{col 55}{space 3}0.000{col 63}{space 4} .2450176{col 76}{space 3} .3570107
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0706008{col 35}{space 2} .0271266{col 46}{space 1}    2.60{col 55}{space 3}0.009{col 63}{space 4} .0173506{col 76}{space 3}  .123851
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2}  .176053{col 35}{space 2} .0391385{col 46}{space 1}    4.50{col 55}{space 3}0.000{col 63}{space 4} .0992234{col 76}{space 3} .2528827
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .2305875{col 35}{space 2} .0374756{col 46}{space 1}    6.15{col 55}{space 3}0.000{col 63}{space 4} .1570222{col 76}{space 3} .3041529
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .299663{col 35}{space 2}  .037307{col 46}{space 1}    8.03{col 55}{space 3}0.000{col 63}{space 4} .2264286{col 76}{space 3} .3728974
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .4441582{col 35}{space 2} .0379672{col 46}{space 1}   11.70{col 55}{space 3}0.000{col 63}{space 4} .3696278{col 76}{space 3} .5186886
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.2148028{col 35}{space 2} .0250914{col 46}{space 1}   -8.56{col 55}{space 3}0.000{col 63}{space 4}-.2640578{col 76}{space 3}-.1655478
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2} -.328739{col 35}{space 2}  .026733{col 46}{space 1}  -12.30{col 55}{space 3}0.000{col 63}{space 4}-.3812164{col 76}{space 3}-.2762616
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2} .3373635{col 35}{space 2} .0531704{col 46}{space 1}    6.34{col 55}{space 3}0.000{col 63}{space 4} .2329889{col 76}{space 3} .4417382
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2} -.049787{col 35}{space 2} .0898739{col 46}{space 1}   -0.55{col 55}{space 3}0.580{col 63}{space 4}-.2262114{col 76}{space 3} .1266374
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.2181655{col 35}{space 2} .0478251{col 46}{space 1}   -4.56{col 55}{space 3}0.000{col 63}{space 4}-.3120472{col 76}{space 3}-.1242838
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0902179{col 35}{space 2} .0450873{col 46}{space 1}    2.00{col 55}{space 3}0.046{col 63}{space 4} .0017105{col 76}{space 3} .1787252
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .2799578{col 35}{space 2} .0467074{col 46}{space 1}    5.99{col 55}{space 3}0.000{col 63}{space 4}   .18827{col 76}{space 3} .3716455
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2} .6643724{col 35}{space 2}   .07648{col 46}{space 1}    8.69{col 55}{space 3}0.000{col 63}{space 4} .5142405{col 76}{space 3} .8145043
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2} -.030283{col 35}{space 2} .0781246{col 46}{space 1}   -0.39{col 55}{space 3}0.698{col 63}{space 4}-.1836432{col 76}{space 3} .1230772
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.2302423{col 35}{space 2} .0760602{col 46}{space 1}   -3.03{col 55}{space 3}0.003{col 63}{space 4}-.3795502{col 76}{space 3}-.0809344
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}  .659009{col 35}{space 2} .0785236{col 46}{space 1}    8.39{col 55}{space 3}0.000{col 63}{space 4} .5048654{col 76}{space 3} .8131525
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.1285516{col 35}{space 2} .0655885{col 46}{space 1}   -1.96{col 55}{space 3}0.050{col 63}{space 4}-.2573033{col 76}{space 3}    .0002
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0184375{col 35}{space 2} .0638086{col 46}{space 1}    0.29{col 55}{space 3}0.773{col 63}{space 4}-.1068202{col 76}{space 3} .1436952
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0843883{col 35}{space 2} .0605854{col 46}{space 1}   -1.39{col 55}{space 3}0.164{col 63}{space 4}-.2033188{col 76}{space 3} .0345423
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.1580676{col 35}{space 2} .0710096{col 46}{space 1}   -2.23{col 55}{space 3}0.026{col 63}{space 4}-.2974609{col 76}{space 3}-.0186742
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0270531{col 35}{space 2} .0854616{col 46}{space 1}   -0.32{col 55}{space 3}0.752{col 63}{space 4} -.194816{col 76}{space 3} .1407098
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.2279393{col 35}{space 2} .0673938{col 46}{space 1}   -3.38{col 55}{space 3}0.001{col 63}{space 4}-.3602348{col 76}{space 3}-.0956439
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.1642085{col 35}{space 2} .0726897{col 46}{space 1}   -2.26{col 55}{space 3}0.024{col 63}{space 4}-.3069001{col 76}{space 3} -.021517
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} -.124714{col 35}{space 2} .0695556{col 46}{space 1}   -1.79{col 55}{space 3}0.073{col 63}{space 4}-.2612531{col 76}{space 3} .0118251
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.1098739{col 35}{space 2} .0602729{col 46}{space 1}   -1.82{col 55}{space 3}0.069{col 63}{space 4}-.2281909{col 76}{space 3} .0084431
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0481873{col 35}{space 2} .0642094{col 46}{space 1}   -0.75{col 55}{space 3}0.453{col 63}{space 4}-.1742317{col 76}{space 3} .0778571
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}-.1109962{col 35}{space 2} .0788101{col 46}{space 1}   -1.41{col 55}{space 3}0.159{col 63}{space 4} -.265702{col 76}{space 3} .0437097
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2} .0793693{col 35}{space 2}  .064347{col 46}{space 1}    1.23{col 55}{space 3}0.218{col 63}{space 4}-.0469453{col 76}{space 3} .2056838
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}  .116625{col 35}{space 2} .0611079{col 46}{space 1}    1.91{col 55}{space 3}0.057{col 63}{space 4}-.0033312{col 76}{space 3} .2365812
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0067934{col 35}{space 2} .0630596{col 46}{space 1}    0.11{col 55}{space 3}0.914{col 63}{space 4} -.116994{col 76}{space 3} .1305807
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0697926{col 35}{space 2} .0606215{col 46}{space 1}   -1.15{col 55}{space 3}0.250{col 63}{space 4}-.1887939{col 76}{space 3} .0492088
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0313231{col 35}{space 2} .0595932{col 46}{space 1}   -0.53{col 55}{space 3}0.599{col 63}{space 4}-.1483058{col 76}{space 3} .0856596
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2}  3.73035{col 35}{space 2}  .065045{col 46}{space 1}   57.35{col 55}{space 3}0.000{col 63}{space 4} 3.602665{col 76}{space 3} 3.858035
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store rank_res
{txt}
{com}.         coefplot rank_res, mcolor(black) ciopts(lcolor(black) lwidth(thin)) xlabel(-.1(.1).5) drop(_cons e_* $townfe) omitted base xline(0) headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in 5-pt Severity Ranking") ytitle("") xsize(5) ysize(7) scale(.6)
{res}{txt}
{com}.         graph export "Tables/rank.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/rank.pdf written in PDF format)

{com}. 
. *******************************************************************************
. *******************************************************************************
. 
. ********        SECTION 4: ANALYSIS FOR ONLINE APPENDIX APPENDIX A      
. 
. *******************************************************************************
. ******************************************************************************* 
.         
. // Open data file where unit of observation is each respondent
.         use "respondent_level_clean.dta", clear
{txt}
{com}.         
. // TABLE 2: Average values of covariates, by occupational group. 
. 
.         eststo summstats: estpost summarize male age education_years daily_income reg_dum presvote 

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:male}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf: .5719794}}}{space 1}{space 1}{ralign 9:{res:{sf:  .245134}}}{space 1}{space 1}{ralign 9:{res:{sf: .4951101}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      445}}}{space 1}
{space 0}{space 0}{ralign 12:age}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      777}}}{space 1}{space 1}{ralign 9:{res:{sf:      777}}}{space 1}{space 1}{ralign 9:{res:{sf: 32.93694}}}{space 1}{space 1}{ralign 9:{res:{sf: 76.89421}}}{space 1}{space 1}{ralign 9:{res:{sf: 8.768935}}}{space 1}{space 1}{ralign 9:{res:{sf:       18}}}{space 1}{space 1}{ralign 9:{res:{sf:       75}}}{space 1}{space 1}{ralign 9:{res:{sf:    25592}}}{space 1}
{space 0}{space 0}{ralign 12:education_~s}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf:  8.61054}}}{space 1}{space 1}{ralign 9:{res:{sf: 12.35907}}}{space 1}{space 1}{ralign 9:{res:{sf: 3.515546}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:       14}}}{space 1}{space 1}{ralign 9:{res:{sf:     6699}}}{space 1}
{space 0}{space 0}{ralign 12:daily_income}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf: 17720.44}}}{space 1}{space 1}{ralign 9:{res:{sf: 4.88e+08}}}{space 1}{space 1}{ralign 9:{res:{sf:  22098.6}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:   200000}}}{space 1}{space 1}{ralign 9:{res:{sf: 1.38e+07}}}{space 1}
{space 0}{space 0}{ralign 12:reg_dum}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf: .9048843}}}{space 1}{space 1}{ralign 9:{res:{sf: .0861795}}}{space 1}{space 1}{ralign 9:{res:{sf: .2935634}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      704}}}{space 1}
{space 0}{space 0}{ralign 12:presvote}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf:      778}}}{space 1}{space 1}{ralign 9:{res:{sf: .8341902}}}{space 1}{space 1}{ralign 9:{res:{sf: .1384949}}}{space 1}{space 1}{ralign 9:{res:{sf:  .372149}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      649}}}{space 1}

{com}.         eststo boda: estpost summarize male age education_years daily_income reg_dum presvote  if boda==1

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:male}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:  .996063}}}{space 1}{space 1}{ralign 9:{res:{sf:  .003937}}}{space 1}{space 1}{ralign 9:{res:{sf: .0627456}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      253}}}{space 1}
{space 0}{space 0}{ralign 12:age}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf: 29.32283}}}{space 1}{space 1}{ralign 9:{res:{sf: 31.14438}}}{space 1}{space 1}{ralign 9:{res:{sf: 5.580715}}}{space 1}{space 1}{ralign 9:{res:{sf:       18}}}{space 1}{space 1}{ralign 9:{res:{sf:       50}}}{space 1}{space 1}{ralign 9:{res:{sf:     7448}}}{space 1}
{space 0}{space 0}{ralign 12:education_~s}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:  8.38189}}}{space 1}{space 1}{ralign 9:{res:{sf:  11.0275}}}{space 1}{space 1}{ralign 9:{res:{sf: 3.320768}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:       14}}}{space 1}{space 1}{ralign 9:{res:{sf:     2129}}}{space 1}
{space 0}{space 0}{ralign 12:daily_income}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf: 11811.02}}}{space 1}{space 1}{ralign 9:{res:{sf: 2.96e+07}}}{space 1}{space 1}{ralign 9:{res:{sf: 5437.728}}}{space 1}{space 1}{ralign 9:{res:{sf:     4000}}}{space 1}{space 1}{ralign 9:{res:{sf:    35000}}}{space 1}{space 1}{ralign 9:{res:{sf:  3000000}}}{space 1}
{space 0}{space 0}{ralign 12:reg_dum}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf: .9173228}}}{space 1}{space 1}{ralign 9:{res:{sf: .0761414}}}{space 1}{space 1}{ralign 9:{res:{sf: .2759373}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      233}}}{space 1}
{space 0}{space 0}{ralign 12:presvote}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf:      254}}}{space 1}{space 1}{ralign 9:{res:{sf: .8503937}}}{space 1}{space 1}{ralign 9:{res:{sf: .1277271}}}{space 1}{space 1}{ralign 9:{res:{sf: .3573893}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      216}}}{space 1}

{com}.         eststo shop: estpost summarize male age education_years daily_income reg_dum presvote  if shopkeeper==1

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:male}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf: .4681648}}}{space 1}{space 1}{ralign 9:{res:{sf: .2499226}}}{space 1}{space 1}{ralign 9:{res:{sf: .4999226}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      125}}}{space 1}
{space 0}{space 0}{ralign 12:age}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      266}}}{space 1}{space 1}{ralign 9:{res:{sf:      266}}}{space 1}{space 1}{ralign 9:{res:{sf: 33.73308}}}{space 1}{space 1}{ralign 9:{res:{sf:    77.57}}}{space 1}{space 1}{ralign 9:{res:{sf: 8.807383}}}{space 1}{space 1}{ralign 9:{res:{sf:       18}}}{space 1}{space 1}{ralign 9:{res:{sf:       64}}}{space 1}{space 1}{ralign 9:{res:{sf:     8973}}}{space 1}
{space 0}{space 0}{ralign 12:education_~s}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf: 9.962547}}}{space 1}{space 1}{ralign 9:{res:{sf: 10.37453}}}{space 1}{space 1}{ralign 9:{res:{sf: 3.220952}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:       14}}}{space 1}{space 1}{ralign 9:{res:{sf:     2660}}}{space 1}
{space 0}{space 0}{ralign 12:daily_income}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf: 24539.33}}}{space 1}{space 1}{ralign 9:{res:{sf: 9.53e+08}}}{space 1}{space 1}{ralign 9:{res:{sf: 30877.66}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:   200000}}}{space 1}{space 1}{ralign 9:{res:{sf:  6552000}}}{space 1}
{space 0}{space 0}{ralign 12:reg_dum}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf: .8801498}}}{space 1}{space 1}{ralign 9:{res:{sf: .1058827}}}{space 1}{space 1}{ralign 9:{res:{sf: .3253962}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      235}}}{space 1}
{space 0}{space 0}{ralign 12:presvote}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf:      267}}}{space 1}{space 1}{ralign 9:{res:{sf: .7902622}}}{space 1}{space 1}{ralign 9:{res:{sf:  .166371}}}{space 1}{space 1}{ralign 9:{res:{sf:  .407886}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      211}}}{space 1}

{com}.         eststo market: estpost summarize male age education_years daily_income reg_dum presvote  if market==1

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:male}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf: .2607004}}}{space 1}{space 1}{ralign 9:{res:{sf: .1934886}}}{space 1}{space 1}{ralign 9:{res:{sf: .4398734}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:       67}}}{space 1}
{space 0}{space 0}{ralign 12:age}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf: 35.68482}}}{space 1}{space 1}{ralign 9:{res:{sf: 100.8104}}}{space 1}{space 1}{ralign 9:{res:{sf: 10.04044}}}{space 1}{space 1}{ralign 9:{res:{sf:       18}}}{space 1}{space 1}{ralign 9:{res:{sf:       75}}}{space 1}{space 1}{ralign 9:{res:{sf:     9171}}}{space 1}
{space 0}{space 0}{ralign 12:education_~s}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf: 7.431907}}}{space 1}{space 1}{ralign 9:{res:{sf:  12.4807}}}{space 1}{space 1}{ralign 9:{res:{sf: 3.532803}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:       14}}}{space 1}{space 1}{ralign 9:{res:{sf:     1910}}}{space 1}
{space 0}{space 0}{ralign 12:daily_income}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf: 16476.65}}}{space 1}{space 1}{ralign 9:{res:{sf: 3.78e+08}}}{space 1}{space 1}{ralign 9:{res:{sf: 19432.46}}}{space 1}{space 1}{ralign 9:{res:{sf:     1000}}}{space 1}{space 1}{ralign 9:{res:{sf:   200000}}}{space 1}{space 1}{ralign 9:{res:{sf:  4234500}}}{space 1}
{space 0}{space 0}{ralign 12:reg_dum}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf: .9182879}}}{space 1}{space 1}{ralign 9:{res:{sf: .0753283}}}{space 1}{space 1}{ralign 9:{res:{sf:   .27446}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      236}}}{space 1}
{space 0}{space 0}{ralign 12:presvote}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf:      257}}}{space 1}{space 1}{ralign 9:{res:{sf: .8638132}}}{space 1}{space 1}{ralign 9:{res:{sf: .1180995}}}{space 1}{space 1}{ralign 9:{res:{sf:  .343656}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      222}}}{space 1}

{com}.         
.         esttab boda shop market using "Tables/sumstats.tex",  replace main(mean %6.2f) aux(sd %6.2f) mtitle("Boda" "Shopkeeper" "Market") 
{res}{txt}(output written to {browse  `"Tables/sumstats.tex"'})

{com}.                 
.                 
.                 
. *******************************************************************************
. *******************************************************************************
. 
. ******** SECTION 5: ANALYSIS FOR ONLINE APPENDIX C (Additional Results: Conjoint Experiment)
. 
. *******************************************************************************
. ******************************************************************************* 
. 
. ********        OPEN DATASET AND SET GLOBALS FOR APPENDICES C1-C3       
.         
.         * Open profile-level dataset
.                 use "profile_level_clean.dta", clear
{txt}
{com}. 
.         * Set globals for analysis: enumerator fixed effects and town fixed effects
.                 gl fe "e_* "
{txt}
{com}.                 gl townfe "townfe_*"
{txt}
{com}.         
.         
. ********        APPENDIX C1: MAIN REGRESSION ANALYSIS   
.         
.         
. // TABLE 3: OLS results of the Conjoint Analysis. This matches the estimates shown in Figure 1
.         reg chosen elect local tax transfer  water health educ infra kinvill buyel $fe $townfe, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    6224
                                                       {txt}F( 35,   777) ={res}   21.88
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0955
                                                       {txt}Root MSE      = {res} .47692

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .0984798{col 26}{space 2} .0137821{col 37}{space 1}    7.15{col 46}{space 3}0.000{col 54}{space 4} .0714252{col 67}{space 3} .1255344
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0160388{col 26}{space 2} .0125061{col 37}{space 1}   -1.28{col 46}{space 3}0.200{col 54}{space 4}-.0405886{col 67}{space 3} .0085109
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2075561{col 26}{space 2} .0162839{col 37}{space 1}   12.75{col 46}{space 3}0.000{col 54}{space 4} .1755904{col 67}{space 3} .2395218
{txt}{space 4}transfer {c |}{col 14}{res}{space 2}  .031053{col 26}{space 2} .0159791{col 37}{space 1}    1.94{col 46}{space 3}0.052{col 54}{space 4}-.0003143{col 67}{space 3} .0624204
{txt}{space 7}water {c |}{col 14}{res}{space 2} .0839465{col 26}{space 2}  .020741{col 37}{space 1}    4.05{col 46}{space 3}0.000{col 54}{space 4} .0432314{col 67}{space 3} .1246616
{txt}{space 6}health {c |}{col 14}{res}{space 2}  .246891{col 26}{space 2} .0202698{col 37}{space 1}   12.18{col 46}{space 3}0.000{col 54}{space 4} .2071009{col 67}{space 3} .2866811
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .1332131{col 26}{space 2} .0198371{col 37}{space 1}    6.72{col 46}{space 3}0.000{col 54}{space 4} .0942724{col 67}{space 3} .1721538
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .0877868{col 26}{space 2} .0200665{col 37}{space 1}    4.37{col 46}{space 3}0.000{col 54}{space 4} .0483958{col 67}{space 3} .1271777
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.1969429{col 26}{space 2} .0154319{col 37}{space 1}  -12.76{col 46}{space 3}0.000{col 54}{space 4}-.2272361{col 67}{space 3}-.1666496
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.1443896{col 26}{space 2} .0157071{col 37}{space 1}   -9.19{col 46}{space 3}0.000{col 54}{space 4} -.175223{col 67}{space 3}-.1135561
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.0190433{col 26}{space 2} .0169886{col 37}{space 1}   -1.12{col 46}{space 3}0.263{col 54}{space 4}-.0523923{col 67}{space 3} .0143057
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.0292991{col 26}{space 2}  .016736{col 37}{space 1}   -1.75{col 46}{space 3}0.080{col 54}{space 4}-.0621523{col 67}{space 3} .0035541
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}-.0077316{col 26}{space 2}  .018219{col 37}{space 1}   -0.42{col 46}{space 3}0.671{col 54}{space 4}-.0434958{col 67}{space 3} .0280326
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2}-.0088587{col 26}{space 2} .0170712{col 37}{space 1}   -0.52{col 46}{space 3}0.604{col 54}{space 4}-.0423698{col 67}{space 3} .0246524
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0067272{col 26}{space 2} .0088482{col 37}{space 1}   -0.76{col 46}{space 3}0.447{col 54}{space 4}-.0240963{col 67}{space 3}  .010642
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.0051728{col 26}{space 2} .0090138{col 37}{space 1}   -0.57{col 46}{space 3}0.566{col 54}{space 4}-.0228672{col 67}{space 3} .0125216
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0065041{col 26}{space 2} .0098327{col 37}{space 1}   -0.66{col 46}{space 3}0.509{col 54}{space 4} -.025806{col 67}{space 3} .0127978
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .0010378{col 26}{space 2}  .009086{col 37}{space 1}    0.11{col 46}{space 3}0.909{col 54}{space 4}-.0167982{col 67}{space 3} .0188738
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.0124806{col 26}{space 2} .0170942{col 37}{space 1}   -0.73{col 46}{space 3}0.466{col 54}{space 4}-.0460368{col 67}{space 3} .0210757
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.0027229{col 26}{space 2} .0140162{col 37}{space 1}   -0.19{col 46}{space 3}0.846{col 54}{space 4}-.0302369{col 67}{space 3} .0247912
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0229239{col 26}{space 2}  .014351{col 37}{space 1}    1.60{col 46}{space 3}0.111{col 54}{space 4}-.0052474{col 67}{space 3} .0510953
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .0021264{col 26}{space 2} .0131352{col 37}{space 1}    0.16{col 46}{space 3}0.871{col 54}{space 4}-.0236583{col 67}{space 3} .0279111
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .0073052{col 26}{space 2} .0120671{col 37}{space 1}    0.61{col 46}{space 3}0.545{col 54}{space 4}-.0163828{col 67}{space 3} .0309933
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}  -.00784{col 26}{space 2} .0125712{col 37}{space 1}   -0.62{col 46}{space 3}0.533{col 54}{space 4}-.0325175{col 67}{space 3} .0168376
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.0037167{col 26}{space 2} .0121873{col 37}{space 1}   -0.30{col 46}{space 3}0.760{col 54}{space 4}-.0276406{col 67}{space 3} .0202071
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0101607{col 26}{space 2} .0122657{col 37}{space 1}    0.83{col 46}{space 3}0.408{col 54}{space 4} -.013917{col 67}{space 3} .0342385
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0002553{col 26}{space 2} .0130245{col 37}{space 1}    0.02{col 46}{space 3}0.984{col 54}{space 4}-.0253121{col 67}{space 3} .0258226
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .0086034{col 26}{space 2} .0132992{col 37}{space 1}    0.65{col 46}{space 3}0.518{col 54}{space 4}-.0175032{col 67}{space 3} .0347101
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}  .006833{col 26}{space 2} .0137347{col 37}{space 1}    0.50{col 46}{space 3}0.619{col 54}{space 4}-.0201284{col 67}{space 3} .0337945
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}  .009343{col 26}{space 2} .0142131{col 37}{space 1}    0.66{col 46}{space 3}0.511{col 54}{space 4}-.0185577{col 67}{space 3} .0372436
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .0165751{col 26}{space 2} .0141332{col 37}{space 1}    1.17{col 46}{space 3}0.241{col 54}{space 4}-.0111687{col 67}{space 3} .0443188
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0169737{col 26}{space 2} .0133134{col 37}{space 1}    1.27{col 46}{space 3}0.203{col 54}{space 4}-.0091607{col 67}{space 3} .0431081
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0066509{col 26}{space 2} .0124681{col 37}{space 1}   -0.53{col 46}{space 3}0.594{col 54}{space 4}-.0311261{col 67}{space 3} .0178242
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0044407{col 26}{space 2} .0127292{col 37}{space 1}    0.35{col 46}{space 3}0.727{col 54}{space 4}-.0205471{col 67}{space 3} .0294285
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .0182892{col 26}{space 2} .0141876{col 37}{space 1}    1.29{col 46}{space 3}0.198{col 54}{space 4}-.0095614{col 67}{space 3} .0461397
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3888625{col 26}{space 2} .0240568{col 37}{space 1}   16.16{col 46}{space 3}0.000{col 54}{space 4} .3416385{col 67}{space 3} .4360865
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/main_results", replace tex(frag) bdec(3) drop(e_* $townfe) ctitle(Chosen) label   
{txt}{stata `"shellout using `"Tables/main_results.tex"'"':Tables/main_results.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/main_results.txt", label"':seeout}

{com}.         reg rank elect local tax transfer water health educ infra kinvill buyel $fe $townfe, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    6224
                                                       {txt}F( 35,   777) ={res}   45.48
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1956
                                                       {txt}Root MSE      = {res} .81032

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1288491{col 26}{space 2} .0227404{col 37}{space 1}    5.67{col 46}{space 3}0.000{col 54}{space 4} .0842092{col 67}{space 3}  .173489
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0133003{col 26}{space 2} .0210879{col 37}{space 1}   -0.63{col 46}{space 3}0.528{col 54}{space 4}-.0546963{col 67}{space 3} .0280958
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .3010142{col 26}{space 2} .0285257{col 37}{space 1}   10.55{col 46}{space 3}0.000{col 54}{space 4} .2450176{col 67}{space 3} .3570107
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0706008{col 26}{space 2} .0271266{col 37}{space 1}    2.60{col 46}{space 3}0.009{col 54}{space 4} .0173506{col 67}{space 3}  .123851
{txt}{space 7}water {c |}{col 14}{res}{space 2}  .176053{col 26}{space 2} .0391385{col 37}{space 1}    4.50{col 46}{space 3}0.000{col 54}{space 4} .0992234{col 67}{space 3} .2528827
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4441582{col 26}{space 2} .0379672{col 37}{space 1}   11.70{col 46}{space 3}0.000{col 54}{space 4} .3696278{col 67}{space 3} .5186886
{txt}{space 8}educ {c |}{col 14}{res}{space 2}  .299663{col 26}{space 2}  .037307{col 37}{space 1}    8.03{col 46}{space 3}0.000{col 54}{space 4} .2264286{col 67}{space 3} .3728974
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .2305875{col 26}{space 2} .0374756{col 37}{space 1}    6.15{col 46}{space 3}0.000{col 54}{space 4} .1570222{col 67}{space 3} .3041529
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2} -.328739{col 26}{space 2}  .026733{col 37}{space 1}  -12.30{col 46}{space 3}0.000{col 54}{space 4}-.3812164{col 67}{space 3}-.2762616
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.2148028{col 26}{space 2} .0250914{col 37}{space 1}   -8.56{col 46}{space 3}0.000{col 54}{space 4}-.2640578{col 67}{space 3}-.1655478
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .3600974{col 26}{space 2} .1113288{col 37}{space 1}    3.23{col 46}{space 3}0.001{col 54}{space 4} .1415567{col 67}{space 3} .5786382
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.1954316{col 26}{space 2} .1060676{col 37}{space 1}   -1.84{col 46}{space 3}0.066{col 54}{space 4}-.4036446{col 67}{space 3} .0127814
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .1129518{col 26}{space 2} .1075996{col 37}{space 1}    1.05{col 46}{space 3}0.294{col 54}{space 4}-.0982685{col 67}{space 3} .3241721
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .3026917{col 26}{space 2} .1037656{col 37}{space 1}    2.92{col 46}{space 3}0.004{col 54}{space 4} .0989976{col 67}{space 3} .5063858
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .7141594{col 26}{space 2} .0659875{col 37}{space 1}   10.82{col 46}{space 3}0.000{col 54}{space 4} .5846244{col 67}{space 3} .8436944
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}  .019504{col 26}{space 2} .0678721{col 37}{space 1}    0.29{col 46}{space 3}0.774{col 54}{space 4}-.1137304{col 67}{space 3} .1527384
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.1804553{col 26}{space 2} .0644828{col 37}{space 1}   -2.80{col 46}{space 3}0.005{col 54}{space 4}-.3070363{col 67}{space 3}-.0538742
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2}  .708796{col 26}{space 2} .0646716{col 37}{space 1}   10.96{col 46}{space 3}0.000{col 54}{space 4} .5818442{col 67}{space 3} .8357477
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .0227339{col 26}{space 2} .1044729{col 37}{space 1}    0.22{col 46}{space 3}0.828{col 54}{space 4}-.1823486{col 67}{space 3} .2278164
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.1014985{col 26}{space 2} .0887062{col 37}{space 1}   -1.14{col 46}{space 3}0.253{col 54}{space 4}-.2756307{col 67}{space 3} .0726337
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0454906{col 26}{space 2} .0869735{col 37}{space 1}    0.52{col 46}{space 3}0.601{col 54}{space 4}-.1252403{col 67}{space 3} .2162214
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0573352{col 26}{space 2} .0847798{col 37}{space 1}   -0.68{col 46}{space 3}0.499{col 54}{space 4}-.2237598{col 67}{space 3} .1090894
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.1580676{col 26}{space 2} .0710096{col 37}{space 1}   -2.23{col 46}{space 3}0.026{col 54}{space 4}-.2974609{col 67}{space 3}-.0186742
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.2279393{col 26}{space 2} .0673938{col 37}{space 1}   -3.38{col 46}{space 3}0.001{col 54}{space 4}-.3602348{col 67}{space 3}-.0956439
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.1642085{col 26}{space 2} .0726897{col 37}{space 1}   -2.26{col 46}{space 3}0.024{col 54}{space 4}-.3069001{col 67}{space 3} -.021517
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} -.124714{col 26}{space 2} .0695556{col 37}{space 1}   -1.79{col 46}{space 3}0.073{col 54}{space 4}-.2612531{col 67}{space 3} .0118251
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.1098739{col 26}{space 2} .0602729{col 37}{space 1}   -1.82{col 46}{space 3}0.069{col 54}{space 4}-.2281909{col 67}{space 3} .0084431
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0211342{col 26}{space 2} .0872679{col 37}{space 1}   -0.24{col 46}{space 3}0.809{col 54}{space 4}-.1924429{col 67}{space 3} .1501745
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.1109962{col 26}{space 2} .0788101{col 37}{space 1}   -1.41{col 46}{space 3}0.159{col 54}{space 4} -.265702{col 67}{space 3} .0437097
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .1064224{col 26}{space 2} .0875542{col 37}{space 1}    1.22{col 46}{space 3}0.225{col 54}{space 4}-.0654484{col 67}{space 3} .2782931
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .1436781{col 26}{space 2} .0851753{col 37}{space 1}    1.69{col 46}{space 3}0.092{col 54}{space 4}-.0235228{col 67}{space 3}  .310879
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0338465{col 26}{space 2} .0864157{col 37}{space 1}    0.39{col 46}{space 3}0.695{col 54}{space 4}-.1357895{col 67}{space 3} .2034824
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0697926{col 26}{space 2} .0606215{col 37}{space 1}   -1.15{col 46}{space 3}0.250{col 54}{space 4}-.1887939{col 67}{space 3} .0492088
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0313231{col 26}{space 2} .0595932{col 37}{space 1}   -0.53{col 46}{space 3}0.599{col 54}{space 4}-.1483058{col 67}{space 3} .0856596
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .0270531{col 26}{space 2} .0854616{col 37}{space 1}    0.32{col 46}{space 3}0.752{col 54}{space 4}-.1407098{col 67}{space 3}  .194816
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.693863{col 26}{space 2} .0812441{col 37}{space 1}   45.47{col 46}{space 3}0.000{col 54}{space 4} 3.534379{col 67}{space 3} 3.853347
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/main_results", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Rank)    label   
{txt}{stata `"shellout using `"Tables/main_results.tex"'"':Tables/main_results.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/main_results.txt", label"':seeout}

{com}. 
. ********        APPENDIX C3: ROBUSTNESS CHECKS
. 
.                 
. // TABLE 4: OLS results for forced-choice analysis, by profile pair 
.         reg chosen elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==1, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}    5.93
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0971
                                                       {txt}Root MSE      = {res} .48071

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .0959074{col 26}{space 2} .0249245{col 37}{space 1}    3.85{col 46}{space 3}0.000{col 54}{space 4}   .04698{col 67}{space 3} .1448348
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0213555{col 26}{space 2} .0245812{col 37}{space 1}   -0.87{col 46}{space 3}0.385{col 54}{space 4}-.0696088{col 67}{space 3} .0268979
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2302572{col 26}{space 2} .0304627{col 37}{space 1}    7.56{col 46}{space 3}0.000{col 54}{space 4} .1704583{col 67}{space 3} .2900561
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0663104{col 26}{space 2} .0314531{col 37}{space 1}    2.11{col 46}{space 3}0.035{col 54}{space 4} .0045672{col 67}{space 3} .1280536
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.1650353{col 26}{space 2} .0308891{col 37}{space 1}   -5.34{col 46}{space 3}0.000{col 54}{space 4}-.2256713{col 67}{space 3}-.1043993
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.1112761{col 26}{space 2} .0309611{col 37}{space 1}   -3.59{col 46}{space 3}0.000{col 54}{space 4}-.1720533{col 67}{space 3}-.0504988
{txt}{space 7}water {c |}{col 14}{res}{space 2} .0799681{col 26}{space 2} .0397965{col 37}{space 1}    2.01{col 46}{space 3}0.045{col 54}{space 4} .0018467{col 67}{space 3} .1580895
{txt}{space 6}health {c |}{col 14}{res}{space 2} .2595205{col 26}{space 2} .0382482{col 37}{space 1}    6.79{col 46}{space 3}0.000{col 54}{space 4} .1844385{col 67}{space 3} .3346025
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .1595568{col 26}{space 2} .0385561{col 37}{space 1}    4.14{col 46}{space 3}0.000{col 54}{space 4} .0838704{col 67}{space 3} .2352432
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .0933138{col 26}{space 2}   .03847{col 37}{space 1}    2.43{col 46}{space 3}0.016{col 54}{space 4} .0177963{col 67}{space 3} .1688312
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.0468628{col 26}{space 2} .0340007{col 37}{space 1}   -1.38{col 46}{space 3}0.169{col 54}{space 4}-.1136069{col 67}{space 3} .0198813
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.0560351{col 26}{space 2} .0334714{col 37}{space 1}   -1.67{col 46}{space 3}0.095{col 54}{space 4}-.1217402{col 67}{space 3}   .00967
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}-.0480524{col 26}{space 2} .0363201{col 37}{space 1}   -1.32{col 46}{space 3}0.186{col 54}{space 4}-.1193495{col 67}{space 3} .0232447
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2}-.0289292{col 26}{space 2} .0356943{col 37}{space 1}   -0.81{col 46}{space 3}0.418{col 54}{space 4}-.0989978{col 67}{space 3} .0411394
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0124391{col 26}{space 2} .0176004{col 37}{space 1}   -0.71{col 46}{space 3}0.480{col 54}{space 4}-.0469891{col 67}{space 3}  .022111
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.0057478{col 26}{space 2} .0180151{col 37}{space 1}   -0.32{col 46}{space 3}0.750{col 54}{space 4}-.0411117{col 67}{space 3} .0296162
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0056806{col 26}{space 2} .0186899{col 37}{space 1}   -0.30{col 46}{space 3}0.761{col 54}{space 4}-.0423694{col 67}{space 3} .0310081
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .0055969{col 26}{space 2} .0173017{col 37}{space 1}    0.32{col 46}{space 3}0.746{col 54}{space 4}-.0283667{col 67}{space 3} .0395604
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.0488462{col 26}{space 2} .0344326{col 37}{space 1}   -1.42{col 46}{space 3}0.156{col 54}{space 4}-.1164382{col 67}{space 3} .0187458
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0140854{col 26}{space 2} .0312829{col 37}{space 1}    0.45{col 46}{space 3}0.653{col 54}{space 4}-.0473236{col 67}{space 3} .0754943
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0531591{col 26}{space 2} .0309099{col 37}{space 1}    1.72{col 46}{space 3}0.086{col 54}{space 4}-.0075178{col 67}{space 3}  .113836
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0008682{col 26}{space 2} .0309202{col 37}{space 1}   -0.03{col 46}{space 3}0.978{col 54}{space 4}-.0615652{col 67}{space 3} .0598289
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0127997{col 26}{space 2} .0211559{col 37}{space 1}   -0.61{col 46}{space 3}0.545{col 54}{space 4}-.0543293{col 67}{space 3} .0287298
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.0355841{col 26}{space 2} .0249085{col 37}{space 1}   -1.43{col 46}{space 3}0.154{col 54}{space 4}  -.08448{col 67}{space 3} .0133118
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2} .0033027{col 26}{space 2} .0237934{col 37}{space 1}    0.14{col 46}{space 3}0.890{col 54}{space 4}-.0434043{col 67}{space 3} .0500096
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.0034483{col 26}{space 2} .0215095{col 37}{space 1}   -0.16{col 46}{space 3}0.873{col 54}{space 4} -.045672{col 67}{space 3} .0387754
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.0073546{col 26}{space 2} .0245871{col 37}{space 1}   -0.30{col 46}{space 3}0.765{col 54}{space 4}-.0556195{col 67}{space 3} .0409104
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .0290259{col 26}{space 2} .0286556{col 37}{space 1}    1.01{col 46}{space 3}0.311{col 54}{space 4}-.0272256{col 67}{space 3} .0852774
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .0106174{col 26}{space 2}  .026104{col 37}{space 1}    0.41{col 46}{space 3}0.684{col 54}{space 4}-.0406253{col 67}{space 3} .0618602
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .0175473{col 26}{space 2} .0292335{col 37}{space 1}    0.60{col 46}{space 3}0.549{col 54}{space 4}-.0398387{col 67}{space 3} .0749334
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .0506363{col 26}{space 2} .0294692{col 37}{space 1}    1.72{col 46}{space 3}0.086{col 54}{space 4}-.0072123{col 67}{space 3} .1084849
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0171912{col 26}{space 2} .0294543{col 37}{space 1}    0.58{col 46}{space 3}0.560{col 54}{space 4}-.0406283{col 67}{space 3} .0750106
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0228983{col 26}{space 2} .0234685{col 37}{space 1}   -0.98{col 46}{space 3}0.330{col 54}{space 4}-.0689675{col 67}{space 3} .0231709
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0089176{col 26}{space 2}  .024887{col 37}{space 1}   -0.36{col 46}{space 3}0.720{col 54}{space 4}-.0577713{col 67}{space 3} .0399361
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .0392443{col 26}{space 2} .0289621{col 37}{space 1}    1.36{col 46}{space 3}0.176{col 54}{space 4}-.0176089{col 67}{space 3} .0960975
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3575454{col 26}{space 2}  .046618{col 37}{space 1}    7.67{col 46}{space 3}0.000{col 54}{space 4} .2660333{col 67}{space 3} .4490575
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof", replace tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 1)        label   
{txt}{stata `"shellout using `"Tables/rob_prof.tex"'"':Tables/rob_prof.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof.txt", label"':seeout}

{com}.         reg chosen elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==2, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}    6.48
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1069
                                                       {txt}Root MSE      = {res} .47808

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2}   .09966{col 26}{space 2} .0242763{col 37}{space 1}    4.11{col 46}{space 3}0.000{col 54}{space 4}  .052005{col 67}{space 3} .1473149
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0357915{col 26}{space 2} .0255207{col 37}{space 1}   -1.40{col 46}{space 3}0.161{col 54}{space 4}-.0858892{col 67}{space 3} .0143062
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2188397{col 26}{space 2} .0304523{col 37}{space 1}    7.19{col 46}{space 3}0.000{col 54}{space 4} .1590611{col 67}{space 3} .2786182
{txt}{space 4}transfer {c |}{col 14}{res}{space 2}   .02597{col 26}{space 2}  .030974{col 37}{space 1}    0.84{col 46}{space 3}0.402{col 54}{space 4}-.0348327{col 67}{space 3} .0867727
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.1885194{col 26}{space 2} .0305925{col 37}{space 1}   -6.16{col 46}{space 3}0.000{col 54}{space 4}-.2485731{col 67}{space 3}-.1284657
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.1326846{col 26}{space 2} .0307304{col 37}{space 1}   -4.32{col 46}{space 3}0.000{col 54}{space 4} -.193009{col 67}{space 3}-.0723602
{txt}{space 7}water {c |}{col 14}{res}{space 2} .0385962{col 26}{space 2} .0402682{col 37}{space 1}    0.96{col 46}{space 3}0.338{col 54}{space 4}-.0404511{col 67}{space 3} .1176435
{txt}{space 6}health {c |}{col 14}{res}{space 2} .2482922{col 26}{space 2} .0369594{col 37}{space 1}    6.72{col 46}{space 3}0.000{col 54}{space 4} .1757401{col 67}{space 3} .3208442
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .0714076{col 26}{space 2} .0398483{col 37}{space 1}    1.79{col 46}{space 3}0.074{col 54}{space 4}-.0068155{col 67}{space 3} .1496307
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .0614136{col 26}{space 2}  .039523{col 37}{space 1}    1.55{col 46}{space 3}0.121{col 54}{space 4}-.0161708{col 67}{space 3} .1389981
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .0051215{col 26}{space 2} .0359284{col 37}{space 1}    0.14{col 46}{space 3}0.887{col 54}{space 4}-.0654068{col 67}{space 3} .0756498
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.0012285{col 26}{space 2}  .037003{col 37}{space 1}   -0.03{col 46}{space 3}0.974{col 54}{space 4}-.0738662{col 67}{space 3} .0714091
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .0263019{col 26}{space 2} .0376077{col 37}{space 1}    0.70{col 46}{space 3}0.485{col 54}{space 4}-.0475228{col 67}{space 3} .1001267
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .0319615{col 26}{space 2} .0358986{col 37}{space 1}    0.89{col 46}{space 3}0.374{col 54}{space 4}-.0385083{col 67}{space 3} .1024313
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0031039{col 26}{space 2} .0199972{col 37}{space 1}   -0.16{col 46}{space 3}0.877{col 54}{space 4}-.0423588{col 67}{space 3} .0361511
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.0187641{col 26}{space 2} .0189549{col 37}{space 1}   -0.99{col 46}{space 3}0.323{col 54}{space 4}-.0559729{col 67}{space 3} .0184448
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0155623{col 26}{space 2} .0203945{col 37}{space 1}   -0.76{col 46}{space 3}0.446{col 54}{space 4}-.0555971{col 67}{space 3} .0244726
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2}-.0099376{col 26}{space 2} .0195112{col 37}{space 1}   -0.51{col 46}{space 3}0.611{col 54}{space 4}-.0482386{col 67}{space 3} .0283633
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .0355504{col 26}{space 2} .0356605{col 37}{space 1}    1.00{col 46}{space 3}0.319{col 54}{space 4} -.034452{col 67}{space 3} .1055527
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.0431277{col 26}{space 2} .0297921{col 37}{space 1}   -1.45{col 46}{space 3}0.148{col 54}{space 4}-.1016102{col 67}{space 3} .0153548
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2}-.0228062{col 26}{space 2} .0307702{col 37}{space 1}   -0.74{col 46}{space 3}0.459{col 54}{space 4}-.0832088{col 67}{space 3} .0375964
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0153572{col 26}{space 2}  .029128{col 37}{space 1}   -0.53{col 46}{space 3}0.598{col 54}{space 4}-.0725362{col 67}{space 3} .0418218
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .0190072{col 26}{space 2} .0256579{col 37}{space 1}    0.74{col 46}{space 3}0.459{col 54}{space 4}-.0313599{col 67}{space 3} .0693742
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} .0183858{col 26}{space 2} .0265149{col 37}{space 1}    0.69{col 46}{space 3}0.488{col 54}{space 4}-.0336636{col 67}{space 3} .0704351
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.0106843{col 26}{space 2} .0249035{col 37}{space 1}   -0.43{col 46}{space 3}0.668{col 54}{space 4}-.0595705{col 67}{space 3} .0382019
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0325114{col 26}{space 2} .0252599{col 37}{space 1}    1.29{col 46}{space 3}0.198{col 54}{space 4}-.0170743{col 67}{space 3} .0820971
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0016475{col 26}{space 2} .0269587{col 37}{space 1}    0.06{col 46}{space 3}0.951{col 54}{space 4} -.051273{col 67}{space 3} .0545679
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0082506{col 26}{space 2}  .028907{col 37}{space 1}   -0.29{col 46}{space 3}0.775{col 54}{space 4}-.0649956{col 67}{space 3} .0484945
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .0143081{col 26}{space 2} .0278159{col 37}{space 1}    0.51{col 46}{space 3}0.607{col 54}{space 4} -.040295{col 67}{space 3} .0689112
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .0040308{col 26}{space 2} .0310512{col 37}{space 1}    0.13{col 46}{space 3}0.897{col 54}{space 4}-.0569234{col 67}{space 3} .0649849
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2}-.0234212{col 26}{space 2} .0313523{col 37}{space 1}   -0.75{col 46}{space 3}0.455{col 54}{space 4}-.0849665{col 67}{space 3} .0381242
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0011023{col 26}{space 2} .0287845{col 37}{space 1}    0.04{col 46}{space 3}0.969{col 54}{space 4}-.0554024{col 67}{space 3}  .057607
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} .0206489{col 26}{space 2} .0243243{col 37}{space 1}    0.85{col 46}{space 3}0.396{col 54}{space 4}-.0271002{col 67}{space 3} .0683979
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0242551{col 26}{space 2} .0253614{col 37}{space 1}    0.96{col 46}{space 3}0.339{col 54}{space 4}  -.02553{col 67}{space 3} .0740402
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2}-.0209878{col 26}{space 2} .0304637{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.0807887{col 67}{space 3}  .038813
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4039857{col 26}{space 2} .0464581{col 37}{space 1}    8.70{col 46}{space 3}0.000{col 54}{space 4} .3127875{col 67}{space 3} .4951839
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 2) label   
{txt}{stata `"shellout using `"Tables/rob_prof.tex"'"':Tables/rob_prof.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof.txt", label"':seeout}

{com}.         reg chosen elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==3, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}    6.70
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1008
                                                       {txt}Root MSE      = {res}  .4797

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .0992861{col 26}{space 2} .0247469{col 37}{space 1}    4.01{col 46}{space 3}0.000{col 54}{space 4} .0507073{col 67}{space 3} .1478648
{txt}{space 7}local {c |}{col 14}{res}{space 2} -.043688{col 26}{space 2}  .024332{col 37}{space 1}   -1.80{col 46}{space 3}0.073{col 54}{space 4}-.0914522{col 67}{space 3} .0040763
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2130164{col 26}{space 2} .0297551{col 37}{space 1}    7.16{col 46}{space 3}0.000{col 54}{space 4} .1546065{col 67}{space 3} .2714264
{txt}{space 4}transfer {c |}{col 14}{res}{space 2}-.0028848{col 26}{space 2} .0308443{col 37}{space 1}   -0.09{col 46}{space 3}0.926{col 54}{space 4}-.0634328{col 67}{space 3} .0576632
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.2043427{col 26}{space 2} .0302123{col 37}{space 1}   -6.76{col 46}{space 3}0.000{col 54}{space 4}-.2636501{col 67}{space 3}-.1450353
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}  -.16611{col 26}{space 2} .0304546{col 37}{space 1}   -5.45{col 46}{space 3}0.000{col 54}{space 4} -.225893{col 67}{space 3} -.106327
{txt}{space 7}water {c |}{col 14}{res}{space 2} .1169596{col 26}{space 2} .0404221{col 37}{space 1}    2.89{col 46}{space 3}0.004{col 54}{space 4} .0376102{col 67}{space 3} .1963091
{txt}{space 6}health {c |}{col 14}{res}{space 2} .2498418{col 26}{space 2} .0383755{col 37}{space 1}    6.51{col 46}{space 3}0.000{col 54}{space 4} .1745098{col 67}{space 3} .3251737
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .1913072{col 26}{space 2} .0382521{col 37}{space 1}    5.00{col 46}{space 3}0.000{col 54}{space 4} .1162175{col 67}{space 3}  .266397
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .1046019{col 26}{space 2} .0377767{col 37}{space 1}    2.77{col 46}{space 3}0.006{col 54}{space 4} .0304454{col 67}{space 3} .1787584
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.0322374{col 26}{space 2} .0379534{col 37}{space 1}   -0.85{col 46}{space 3}0.396{col 54}{space 4}-.1067407{col 67}{space 3} .0422659
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.0324772{col 26}{space 2} .0360942{col 37}{space 1}   -0.90{col 46}{space 3}0.369{col 54}{space 4}-.1033309{col 67}{space 3} .0383766
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .0054289{col 26}{space 2} .0398959{col 37}{space 1}    0.14{col 46}{space 3}0.892{col 54}{space 4}-.0728877{col 67}{space 3} .0837454
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2}-.0159725{col 26}{space 2} .0379505{col 37}{space 1}   -0.42{col 46}{space 3}0.674{col 54}{space 4}-.0904703{col 67}{space 3} .0585252
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0071793{col 26}{space 2} .0199109{col 37}{space 1}   -0.36{col 46}{space 3}0.719{col 54}{space 4}-.0462648{col 67}{space 3} .0319062
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}  .022002{col 26}{space 2} .0202907{col 37}{space 1}    1.08{col 46}{space 3}0.279{col 54}{space 4}-.0178291{col 67}{space 3}  .061833
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0121477{col 26}{space 2} .0218405{col 37}{space 1}   -0.56{col 46}{space 3}0.578{col 54}{space 4}-.0550212{col 67}{space 3} .0307258
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2}-.0062269{col 26}{space 2} .0190031{col 37}{space 1}   -0.33{col 46}{space 3}0.743{col 54}{space 4}-.0435304{col 67}{space 3} .0310766
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.0274447{col 26}{space 2}  .036854{col 37}{space 1}   -0.74{col 46}{space 3}0.457{col 54}{space 4}-.0997899{col 67}{space 3} .0449005
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0082492{col 26}{space 2} .0311043{col 37}{space 1}    0.27{col 46}{space 3}0.791{col 54}{space 4}-.0528093{col 67}{space 3} .0693077
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0342307{col 26}{space 2} .0315938{col 37}{space 1}    1.08{col 46}{space 3}0.279{col 54}{space 4}-.0277886{col 67}{space 3}   .09625
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .0207945{col 26}{space 2} .0319046{col 37}{space 1}    0.65{col 46}{space 3}0.515{col 54}{space 4}-.0418349{col 67}{space 3} .0834238
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .0179375{col 26}{space 2} .0241053{col 37}{space 1}    0.74{col 46}{space 3}0.457{col 54}{space 4}-.0293818{col 67}{space 3} .0652568
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.0246092{col 26}{space 2} .0232284{col 37}{space 1}   -1.06{col 46}{space 3}0.290{col 54}{space 4}-.0702071{col 67}{space 3} .0209887
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}  .002891{col 26}{space 2} .0237476{col 37}{space 1}    0.12{col 46}{space 3}0.903{col 54}{space 4}-.0437262{col 67}{space 3} .0495081
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.0079052{col 26}{space 2} .0243521{col 37}{space 1}   -0.32{col 46}{space 3}0.746{col 54}{space 4}-.0557088{col 67}{space 3} .0398984
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0017919{col 26}{space 2} .0253901{col 37}{space 1}    0.07{col 46}{space 3}0.944{col 54}{space 4}-.0480494{col 67}{space 3} .0516332
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0147899{col 26}{space 2} .0327158{col 37}{space 1}   -0.45{col 46}{space 3}0.651{col 54}{space 4}-.0790118{col 67}{space 3}  .049432
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .0068286{col 26}{space 2} .0273675{col 37}{space 1}    0.25{col 46}{space 3}0.803{col 54}{space 4}-.0468945{col 67}{space 3} .0605517
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .0194045{col 26}{space 2} .0325676{col 37}{space 1}    0.60{col 46}{space 3}0.551{col 54}{space 4}-.0445264{col 67}{space 3} .0833353
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2}-.0060597{col 26}{space 2} .0321736{col 37}{space 1}   -0.19{col 46}{space 3}0.851{col 54}{space 4}-.0692171{col 67}{space 3} .0570978
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0227208{col 26}{space 2} .0320105{col 37}{space 1}    0.71{col 46}{space 3}0.478{col 54}{space 4}-.0401165{col 67}{space 3} .0855581
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0224558{col 26}{space 2} .0258742{col 37}{space 1}   -0.87{col 46}{space 3}0.386{col 54}{space 4}-.0732474{col 67}{space 3} .0283358
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0068975{col 26}{space 2}   .02321{col 37}{space 1}    0.30{col 46}{space 3}0.766{col 54}{space 4}-.0386643{col 67}{space 3} .0524592
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2}   .02128{col 26}{space 2} .0302917{col 37}{space 1}    0.70{col 46}{space 3}0.483{col 54}{space 4}-.0381833{col 67}{space 3} .0807433
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4041113{col 26}{space 2} .0456976{col 37}{space 1}    8.84{col 46}{space 3}0.000{col 54}{space 4}  .314406{col 67}{space 3} .4938167
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 3) label   
{txt}{stata `"shellout using `"Tables/rob_prof.tex"'"':Tables/rob_prof.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof.txt", label"':seeout}

{com}.         reg chosen elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==4, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}    6.06
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0955
                                                       {txt}Root MSE      = {res} .48113

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1025386{col 26}{space 2} .0245232{col 37}{space 1}    4.18{col 46}{space 3}0.000{col 54}{space 4} .0543991{col 67}{space 3} .1506781
{txt}{space 7}local {c |}{col 14}{res}{space 2} .0357891{col 26}{space 2} .0244099{col 37}{space 1}    1.47{col 46}{space 3}0.143{col 54}{space 4} -.012128{col 67}{space 3} .0837062
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .1754054{col 26}{space 2} .0307589{col 37}{space 1}    5.70{col 46}{space 3}0.000{col 54}{space 4} .1150251{col 67}{space 3} .2357857
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0333076{col 26}{space 2} .0307676{col 37}{space 1}    1.08{col 46}{space 3}0.279{col 54}{space 4}-.0270899{col 67}{space 3} .0937052
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.2409795{col 26}{space 2} .0298908{col 37}{space 1}   -8.06{col 46}{space 3}0.000{col 54}{space 4}-.2996557{col 67}{space 3}-.1823033
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.1749625{col 26}{space 2} .0299298{col 37}{space 1}   -5.85{col 46}{space 3}0.000{col 54}{space 4}-.2337153{col 67}{space 3}-.1162097
{txt}{space 7}water {c |}{col 14}{res}{space 2} .1003909{col 26}{space 2} .0389601{col 37}{space 1}    2.58{col 46}{space 3}0.010{col 54}{space 4} .0239114{col 67}{space 3} .1768704
{txt}{space 6}health {c |}{col 14}{res}{space 2} .2402915{col 26}{space 2} .0387406{col 37}{space 1}    6.20{col 46}{space 3}0.000{col 54}{space 4} .1642429{col 67}{space 3} .3163401
{txt}{space 8}educ {c |}{col 14}{res}{space 2}  .118674{col 26}{space 2} .0384104{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .0432735{col 67}{space 3} .1940745
{txt}{space 7}infra {c |}{col 14}{res}{space 2}  .096714{col 26}{space 2} .0380146{col 37}{space 1}    2.54{col 46}{space 3}0.011{col 54}{space 4} .0220906{col 67}{space 3} .1713374
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .0329656{col 26}{space 2} .0285862{col 37}{space 1}    1.15{col 46}{space 3}0.249{col 54}{space 4}-.0231498{col 67}{space 3} .0890811
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.0032639{col 26}{space 2} .0284899{col 37}{space 1}   -0.11{col 46}{space 3}0.909{col 54}{space 4}-.0591902{col 67}{space 3} .0526625
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .0165357{col 26}{space 2}  .030807{col 37}{space 1}    0.54{col 46}{space 3}0.592{col 54}{space 4} -.043939{col 67}{space 3} .0770104
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .0066758{col 26}{space 2} .0290621{col 37}{space 1}    0.23{col 46}{space 3}0.818{col 54}{space 4}-.0503738{col 67}{space 3} .0637254
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .0001438{col 26}{space 2} .0182485{col 37}{space 1}    0.01{col 46}{space 3}0.994{col 54}{space 4}-.0356784{col 67}{space 3} .0359661
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.0047266{col 26}{space 2} .0181581{col 37}{space 1}   -0.26{col 46}{space 3}0.795{col 54}{space 4}-.0403712{col 67}{space 3} .0309181
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2} .0170443{col 26}{space 2} .0206503{col 37}{space 1}    0.83{col 46}{space 3}0.409{col 54}{space 4}-.0234926{col 67}{space 3} .0575812
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .0182871{col 26}{space 2} .0192802{col 37}{space 1}    0.95{col 46}{space 3}0.343{col 54}{space 4}-.0195603{col 67}{space 3} .0561346
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .0183891{col 26}{space 2}  .028517{col 37}{space 1}    0.64{col 46}{space 3}0.519{col 54}{space 4}-.0375905{col 67}{space 3} .0743687
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0131159{col 26}{space 2} .0215467{col 37}{space 1}    0.61{col 46}{space 3}0.543{col 54}{space 4}-.0291807{col 67}{space 3} .0554125
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0174709{col 26}{space 2} .0239087{col 37}{space 1}    0.73{col 46}{space 3}0.465{col 54}{space 4}-.0294624{col 67}{space 3} .0644042
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0104916{col 26}{space 2} .0244631{col 37}{space 1}   -0.43{col 46}{space 3}0.668{col 54}{space 4}-.0585133{col 67}{space 3}   .03753
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .0349657{col 26}{space 2} .0256996{col 37}{space 1}    1.36{col 46}{space 3}0.174{col 54}{space 4}-.0154832{col 67}{space 3} .0854146
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}  .024911{col 26}{space 2} .0248452{col 37}{space 1}    1.00{col 46}{space 3}0.316{col 54}{space 4}-.0238606{col 67}{space 3} .0736826
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2} .0066143{col 26}{space 2} .0237124{col 37}{space 1}    0.28{col 46}{space 3}0.780{col 54}{space 4}-.0399336{col 67}{space 3} .0531621
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0271748{col 26}{space 2} .0236289{col 37}{space 1}    1.15{col 46}{space 3}0.250{col 54}{space 4}-.0192091{col 67}{space 3} .0735588
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0303948{col 26}{space 2} .0244459{col 37}{space 1}    1.24{col 46}{space 3}0.214{col 54}{space 4}-.0175929{col 67}{space 3} .0783826
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .0338244{col 26}{space 2} .0243195{col 37}{space 1}    1.39{col 46}{space 3}0.165{col 54}{space 4}-.0139153{col 67}{space 3} .0815641
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .0239293{col 26}{space 2} .0237612{col 37}{space 1}    1.01{col 46}{space 3}0.314{col 54}{space 4}-.0227145{col 67}{space 3} .0705731
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}-.0025496{col 26}{space 2} .0226154{col 37}{space 1}   -0.11{col 46}{space 3}0.910{col 54}{space 4}-.0469442{col 67}{space 3}  .041845
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .0367647{col 26}{space 2} .0236976{col 37}{space 1}    1.55{col 46}{space 3}0.121{col 54}{space 4}-.0097542{col 67}{space 3} .0832837
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0108481{col 26}{space 2} .0222423{col 37}{space 1}    0.49{col 46}{space 3}0.626{col 54}{space 4}-.0328141{col 67}{space 3} .0545103
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} .0153376{col 26}{space 2} .0243452{col 37}{space 1}    0.63{col 46}{space 3}0.529{col 54}{space 4}-.0324526{col 67}{space 3} .0631279
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0231693{col 26}{space 2} .0248291{col 37}{space 1}    0.93{col 46}{space 3}0.351{col 54}{space 4}-.0255707{col 67}{space 3} .0719094
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .0278215{col 26}{space 2} .0220697{col 37}{space 1}    1.26{col 46}{space 3}0.208{col 54}{space 4}-.0155017{col 67}{space 3} .0711447
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3634537{col 26}{space 2} .0435368{col 37}{space 1}    8.35{col 46}{space 3}0.000{col 54}{space 4} .2779901{col 67}{space 3} .4489174
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 4) label   
{txt}{stata `"shellout using `"Tables/rob_prof.tex"'"':Tables/rob_prof.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof.txt", label"':seeout}

{com}. 
.                 
.                 
. // TABLE 5: OLS results for 5-point severity ranking analysis, by profile pair 
.         reg rank elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==1, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}   16.11
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.2189
                                                       {txt}Root MSE      = {res} .85831

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1529099{col 26}{space 2} .0442468{col 37}{space 1}    3.46{col 46}{space 3}0.001{col 54}{space 4} .0660525{col 67}{space 3} .2397673
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0006646{col 26}{space 2} .0453083{col 37}{space 1}   -0.01{col 46}{space 3}0.988{col 54}{space 4}-.0896057{col 67}{space 3} .0882765
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .3529384{col 26}{space 2} .0540075{col 37}{space 1}    6.53{col 46}{space 3}0.000{col 54}{space 4} .2469204{col 67}{space 3} .4589564
{txt}{space 4}transfer {c |}{col 14}{res}{space 2}  .100324{col 26}{space 2} .0554811{col 37}{space 1}    1.81{col 46}{space 3}0.071{col 54}{space 4}-.0085867{col 67}{space 3} .2092347
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}  -.33139{col 26}{space 2}  .055771{col 37}{space 1}   -5.94{col 46}{space 3}0.000{col 54}{space 4}-.4408698{col 67}{space 3}-.2219103
{txt}{space 7}buyel {c |}{col 14}{res}{space 2} -.179641{col 26}{space 2} .0516807{col 37}{space 1}   -3.48{col 46}{space 3}0.001{col 54}{space 4}-.2810913{col 67}{space 3}-.0781906
{txt}{space 7}water {c |}{col 14}{res}{space 2} .2188163{col 26}{space 2}   .07619{col 37}{space 1}    2.87{col 46}{space 3}0.004{col 54}{space 4} .0692537{col 67}{space 3} .3683789
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4885368{col 26}{space 2}  .073398{col 37}{space 1}    6.66{col 46}{space 3}0.000{col 54}{space 4} .3444549{col 67}{space 3} .6326187
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .3980161{col 26}{space 2} .0729898{col 37}{space 1}    5.45{col 46}{space 3}0.000{col 54}{space 4} .2547356{col 67}{space 3} .5412967
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .2725001{col 26}{space 2} .0753817{col 37}{space 1}    3.61{col 46}{space 3}0.000{col 54}{space 4} .1245243{col 67}{space 3}  .420476
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .3792623{col 26}{space 2} .1925719{col 37}{space 1}    1.97{col 46}{space 3}0.049{col 54}{space 4} .0012395{col 67}{space 3}  .757285
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.3740333{col 26}{space 2} .1827328{col 37}{space 1}   -2.05{col 46}{space 3}0.041{col 54}{space 4}-.7327418{col 67}{space 3}-.0153248
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .1920944{col 26}{space 2} .1896594{col 37}{space 1}    1.01{col 46}{space 3}0.311{col 54}{space 4}-.1802112{col 67}{space 3} .5643999
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .2063547{col 26}{space 2} .1827432{col 37}{space 1}    1.13{col 46}{space 3}0.259{col 54}{space 4}-.1523742{col 67}{space 3} .5650836
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .8917795{col 26}{space 2} .1086746{col 37}{space 1}    8.21{col 46}{space 3}0.000{col 54}{space 4} .6784489{col 67}{space 3}  1.10511
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} .1520485{col 26}{space 2} .1166431{col 37}{space 1}    1.30{col 46}{space 3}0.193{col 54}{space 4}-.0769245{col 67}{space 3} .3810215
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0620531{col 26}{space 2} .1112937{col 37}{space 1}   -0.56{col 46}{space 3}0.577{col 54}{space 4} -.280525{col 67}{space 3} .1564188
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .8501419{col 26}{space 2} .1068416{col 37}{space 1}    7.96{col 46}{space 3}0.000{col 54}{space 4} .6404095{col 67}{space 3} 1.059874
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .0340342{col 26}{space 2} .1851793{col 37}{space 1}    0.18{col 46}{space 3}0.854{col 54}{space 4}-.3294769{col 67}{space 3} .3975452
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0972269{col 26}{space 2} .1684329{col 37}{space 1}    0.58{col 46}{space 3}0.564{col 54}{space 4}-.2334105{col 67}{space 3} .4278643
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .1924955{col 26}{space 2} .1616313{col 37}{space 1}    1.19{col 46}{space 3}0.234{col 54}{space 4}-.1247902{col 67}{space 3} .5097812
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .1315879{col 26}{space 2} .1640085{col 37}{space 1}    0.80{col 46}{space 3}0.423{col 54}{space 4}-.1903645{col 67}{space 3} .4535402
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.1788079{col 26}{space 2} .1157184{col 37}{space 1}   -1.55{col 46}{space 3}0.123{col 54}{space 4}-.4059656{col 67}{space 3} .0483498
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.2305353{col 26}{space 2} .1263734{col 37}{space 1}   -1.82{col 46}{space 3}0.068{col 54}{space 4} -.478609{col 67}{space 3} .0175384
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.1800657{col 26}{space 2} .1102028{col 37}{space 1}   -1.63{col 46}{space 3}0.103{col 54}{space 4}-.3963962{col 67}{space 3} .0362648
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.1217537{col 26}{space 2} .1038901{col 37}{space 1}   -1.17{col 46}{space 3}0.242{col 54}{space 4}-.3256923{col 67}{space 3} .0821848
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} -.068217{col 26}{space 2} .1065951{col 37}{space 1}   -0.64{col 46}{space 3}0.522{col 54}{space 4}-.2774655{col 67}{space 3} .1410314
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .0383534{col 26}{space 2} .1625251{col 37}{space 1}    0.24{col 46}{space 3}0.814{col 54}{space 4}-.2806869{col 67}{space 3} .3573936
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.1050384{col 26}{space 2} .1325977{col 37}{space 1}   -0.79{col 46}{space 3}0.429{col 54}{space 4}-.3653305{col 67}{space 3} .1552538
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .2076549{col 26}{space 2} .1711705{col 37}{space 1}    1.21{col 46}{space 3}0.225{col 54}{space 4}-.1283566{col 67}{space 3} .5436664
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .2058271{col 26}{space 2} .1662892{col 37}{space 1}    1.24{col 46}{space 3}0.216{col 54}{space 4}-.1206023{col 67}{space 3} .5322565
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0767856{col 26}{space 2} .1585683{col 37}{space 1}    0.48{col 46}{space 3}0.628{col 54}{space 4}-.2344873{col 67}{space 3} .3880586
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} -.030597{col 26}{space 2} .1011989{col 37}{space 1}   -0.30{col 46}{space 3}0.762{col 54}{space 4}-.2292526{col 67}{space 3} .1680586
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0780251{col 26}{space 2} .1105447{col 37}{space 1}   -0.71{col 46}{space 3}0.481{col 54}{space 4}-.2950268{col 67}{space 3} .1389767
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2}  .184855{col 26}{space 2} .1578686{col 37}{space 1}    1.17{col 46}{space 3}0.242{col 54}{space 4}-.1250446{col 67}{space 3} .4947546
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.370579{col 26}{space 2} .1391627{col 37}{space 1}   24.22{col 46}{space 3}0.000{col 54}{space 4} 3.097399{col 67}{space 3} 3.643758
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof_rk", replace tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 1)     label   
{txt}{stata `"shellout using `"Tables/rob_prof_rk.tex"'"':Tables/rob_prof_rk.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof_rk.txt", label"':seeout}

{com}.         reg rank elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==2, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}   17.12
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.2039
                                                       {txt}Root MSE      = {res} .78592

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1080917{col 26}{space 2} .0415573{col 37}{space 1}    2.60{col 46}{space 3}0.009{col 54}{space 4} .0265139{col 67}{space 3} .1896695
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0247796{col 26}{space 2} .0394059{col 37}{space 1}   -0.63{col 46}{space 3}0.530{col 54}{space 4}-.1021343{col 67}{space 3}  .052575
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .3207767{col 26}{space 2} .0494575{col 37}{space 1}    6.49{col 46}{space 3}0.000{col 54}{space 4} .2236906{col 67}{space 3} .4178629
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0544213{col 26}{space 2} .0498209{col 37}{space 1}    1.09{col 46}{space 3}0.275{col 54}{space 4}-.0433782{col 67}{space 3} .1522207
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.2893794{col 26}{space 2}  .049692{col 37}{space 1}   -5.82{col 46}{space 3}0.000{col 54}{space 4} -.386926{col 67}{space 3}-.1918329
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.2098928{col 26}{space 2} .0474521{col 37}{space 1}   -4.42{col 46}{space 3}0.000{col 54}{space 4}-.3030423{col 67}{space 3}-.1167434
{txt}{space 7}water {c |}{col 14}{res}{space 2}  .128596{col 26}{space 2} .0701413{col 37}{space 1}    1.83{col 46}{space 3}0.067{col 54}{space 4}-.0090928{col 67}{space 3} .2662848
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4205324{col 26}{space 2} .0650093{col 37}{space 1}    6.47{col 46}{space 3}0.000{col 54}{space 4} .2929178{col 67}{space 3} .5481471
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .2245654{col 26}{space 2} .0674595{col 37}{space 1}    3.33{col 46}{space 3}0.001{col 54}{space 4}  .092141{col 67}{space 3} .3569898
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .2007225{col 26}{space 2} .0659388{col 37}{space 1}    3.04{col 46}{space 3}0.002{col 54}{space 4} .0712832{col 67}{space 3} .3301619
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .3645205{col 26}{space 2} .1759039{col 37}{space 1}    2.07{col 46}{space 3}0.039{col 54}{space 4} .0192173{col 67}{space 3} .7098236
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.2626364{col 26}{space 2} .1761489{col 37}{space 1}   -1.49{col 46}{space 3}0.136{col 54}{space 4}-.6084205{col 67}{space 3} .0831476
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .1019985{col 26}{space 2}  .175564{col 37}{space 1}    0.58{col 46}{space 3}0.561{col 54}{space 4}-.2426375{col 67}{space 3} .4466345
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .3023625{col 26}{space 2} .1730895{col 37}{space 1}    1.75{col 46}{space 3}0.081{col 54}{space 4}-.0374159{col 67}{space 3} .6421408
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .6972938{col 26}{space 2}  .080018{col 37}{space 1}    8.71{col 46}{space 3}0.000{col 54}{space 4} .5402166{col 67}{space 3} .8543709
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} .0852116{col 26}{space 2} .0848215{col 37}{space 1}    1.00{col 46}{space 3}0.315{col 54}{space 4}-.0812948{col 67}{space 3}  .251718
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.1756016{col 26}{space 2} .0876307{col 37}{space 1}   -2.00{col 46}{space 3}0.045{col 54}{space 4}-.3476226{col 67}{space 3}-.0035807
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .6588377{col 26}{space 2} .0778284{col 37}{space 1}    8.47{col 46}{space 3}0.000{col 54}{space 4} .5060589{col 67}{space 3} .8116165
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .0181708{col 26}{space 2} .1698414{col 37}{space 1}    0.11{col 46}{space 3}0.915{col 54}{space 4}-.3152315{col 67}{space 3} .3515732
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0082398{col 26}{space 2} .1488182{col 37}{space 1}    0.06{col 46}{space 3}0.956{col 54}{space 4}-.2838935{col 67}{space 3} .3003731
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0089324{col 26}{space 2} .1467396{col 37}{space 1}    0.06{col 46}{space 3}0.951{col 54}{space 4}-.2791206{col 67}{space 3} .2969855
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .0042331{col 26}{space 2} .1495511{col 37}{space 1}    0.03{col 46}{space 3}0.977{col 54}{space 4}-.2893389{col 67}{space 3} .2978051
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0724911{col 26}{space 2} .1132168{col 37}{space 1}   -0.64{col 46}{space 3}0.522{col 54}{space 4}-.2947382{col 67}{space 3} .1497559
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.2161368{col 26}{space 2} .1090339{col 37}{space 1}   -1.98{col 46}{space 3}0.048{col 54}{space 4}-.4301727{col 67}{space 3}-.0021009
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.0489488{col 26}{space 2} .1235386{col 37}{space 1}   -0.40{col 46}{space 3}0.692{col 54}{space 4}-.2914578{col 67}{space 3} .1935602
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.0921051{col 26}{space 2}  .113046{col 37}{space 1}   -0.81{col 46}{space 3}0.415{col 54}{space 4}-.3140169{col 67}{space 3} .1298067
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.0250121{col 26}{space 2} .1078934{col 37}{space 1}   -0.23{col 46}{space 3}0.817{col 54}{space 4}-.2368093{col 67}{space 3} .1867851
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .0747579{col 26}{space 2} .1506874{col 37}{space 1}    0.50{col 46}{space 3}0.620{col 54}{space 4}-.2210447{col 67}{space 3} .3705605
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .0382658{col 26}{space 2} .1211119{col 37}{space 1}    0.32{col 46}{space 3}0.752{col 54}{space 4}-.1994795{col 67}{space 3}  .276011
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .2587534{col 26}{space 2} .1511774{col 37}{space 1}    1.71{col 46}{space 3}0.087{col 54}{space 4}-.0380111{col 67}{space 3}  .555518
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .1456285{col 26}{space 2}  .146901{col 37}{space 1}    0.99{col 46}{space 3}0.322{col 54}{space 4}-.1427413{col 67}{space 3} .4339983
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .1269181{col 26}{space 2} .1405069{col 37}{space 1}    0.90{col 46}{space 3}0.367{col 54}{space 4}   -.1489{col 67}{space 3} .4027361
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0247008{col 26}{space 2} .1062347{col 37}{space 1}   -0.23{col 46}{space 3}0.816{col 54}{space 4}-.2332419{col 67}{space 3} .1838403
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0389536{col 26}{space 2} .1062702{col 37}{space 1}    0.37{col 46}{space 3}0.714{col 54}{space 4}-.1696572{col 67}{space 3} .2475644
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .0865875{col 26}{space 2} .1415403{col 37}{space 1}    0.61{col 46}{space 3}0.541{col 54}{space 4}-.1912593{col 67}{space 3} .3644342
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.663323{col 26}{space 2} .1308315{col 37}{space 1}   28.00{col 46}{space 3}0.000{col 54}{space 4} 3.406498{col 67}{space 3} 3.920148
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof_rk", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 2)      label   
{txt}{stata `"shellout using `"Tables/rob_prof_rk.tex"'"':Tables/rob_prof_rk.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof_rk.txt", label"':seeout}

{com}.         reg rank elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==3, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}   16.04
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.2078
                                                       {txt}Root MSE      = {res} .80067

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .0970431{col 26}{space 2} .0423232{col 37}{space 1}    2.29{col 46}{space 3}0.022{col 54}{space 4} .0139619{col 67}{space 3} .1801244
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0497946{col 26}{space 2} .0411112{col 37}{space 1}   -1.21{col 46}{space 3}0.226{col 54}{space 4}-.1304968{col 67}{space 3} .0309076
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .3109598{col 26}{space 2} .0500738{col 37}{space 1}    6.21{col 46}{space 3}0.000{col 54}{space 4} .2126639{col 67}{space 3} .4092557
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0418387{col 26}{space 2} .0524697{col 37}{space 1}    0.80{col 46}{space 3}0.425{col 54}{space 4}-.0611605{col 67}{space 3} .1448378
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2} -.346138{col 26}{space 2}  .051098{col 37}{space 1}   -6.77{col 46}{space 3}0.000{col 54}{space 4}-.4464445{col 67}{space 3}-.2458315
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.2497349{col 26}{space 2} .0510845{col 37}{space 1}   -4.89{col 46}{space 3}0.000{col 54}{space 4}-.3500149{col 67}{space 3}-.1494549
{txt}{space 7}water {c |}{col 14}{res}{space 2} .2320418{col 26}{space 2} .0697793{col 37}{space 1}    3.33{col 46}{space 3}0.001{col 54}{space 4} .0950635{col 67}{space 3} .3690202
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4617343{col 26}{space 2} .0718339{col 37}{space 1}    6.43{col 46}{space 3}0.000{col 54}{space 4} .3207227{col 67}{space 3} .6027458
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .3657273{col 26}{space 2} .0676242{col 37}{space 1}    5.41{col 46}{space 3}0.000{col 54}{space 4} .2329794{col 67}{space 3} .4984751
{txt}{space 7}infra {c |}{col 14}{res}{space 2}  .261671{col 26}{space 2} .0643754{col 37}{space 1}    4.06{col 46}{space 3}0.000{col 54}{space 4} .1353007{col 67}{space 3} .3880413
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .1530337{col 26}{space 2} .1748216{col 37}{space 1}    0.88{col 46}{space 3}0.382{col 54}{space 4}-.1901448{col 67}{space 3} .4962123
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2} -.308721{col 26}{space 2}  .182108{col 37}{space 1}   -1.70{col 46}{space 3}0.090{col 54}{space 4} -.666203{col 67}{space 3} .0487609
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .0232109{col 26}{space 2} .1796969{col 37}{space 1}    0.13{col 46}{space 3}0.897{col 54}{space 4}-.3295381{col 67}{space 3} .3759598
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .2447069{col 26}{space 2} .1800182{col 37}{space 1}    1.36{col 46}{space 3}0.174{col 54}{space 4}-.1086728{col 67}{space 3} .5980866
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .6181743{col 26}{space 2} .0899003{col 37}{space 1}    6.88{col 46}{space 3}0.000{col 54}{space 4} .4416981{col 67}{space 3} .7946505
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.1150608{col 26}{space 2} .0981624{col 37}{space 1}   -1.17{col 46}{space 3}0.241{col 54}{space 4}-.3077557{col 67}{space 3} .0776341
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2} -.242622{col 26}{space 2} .0990908{col 37}{space 1}   -2.45{col 46}{space 3}0.015{col 54}{space 4}-.4371394{col 67}{space 3}-.0481046
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .6413625{col 26}{space 2} .0915429{col 37}{space 1}    7.01{col 46}{space 3}0.000{col 54}{space 4} .4616618{col 67}{space 3} .8210631
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.1315407{col 26}{space 2} .1704492{col 37}{space 1}   -0.77{col 46}{space 3}0.441{col 54}{space 4}-.4661362{col 67}{space 3} .2030547
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.1377479{col 26}{space 2}  .171045{col 37}{space 1}   -0.81{col 46}{space 3}0.421{col 54}{space 4} -.473513{col 67}{space 3} .1980171
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0170602{col 26}{space 2} .1559223{col 37}{space 1}    0.11{col 46}{space 3}0.913{col 54}{space 4}-.2890187{col 67}{space 3}  .323139
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0554301{col 26}{space 2} .1582123{col 37}{space 1}   -0.35{col 46}{space 3}0.726{col 54}{space 4}-.3660043{col 67}{space 3} .2551442
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.2606133{col 26}{space 2} .1059871{col 37}{space 1}   -2.46{col 46}{space 3}0.014{col 54}{space 4}-.4686683{col 67}{space 3}-.0525583
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.3100712{col 26}{space 2} .1017688{col 37}{space 1}   -3.05{col 46}{space 3}0.002{col 54}{space 4}-.5098456{col 67}{space 3}-.1102967
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.2408542{col 26}{space 2} .1061167{col 37}{space 1}   -2.27{col 46}{space 3}0.023{col 54}{space 4}-.4491637{col 67}{space 3}-.0325447
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.2130888{col 26}{space 2} .0966043{col 37}{space 1}   -2.21{col 46}{space 3}0.028{col 54}{space 4}-.4027252{col 67}{space 3}-.0234523
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.2595764{col 26}{space 2} .1018371{col 37}{space 1}   -2.55{col 46}{space 3}0.011{col 54}{space 4}-.4594847{col 67}{space 3} -.059668
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0915059{col 26}{space 2}  .159662{col 37}{space 1}   -0.57{col 46}{space 3}0.567{col 54}{space 4}-.4049258{col 67}{space 3} .2219141
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.1413022{col 26}{space 2} .1122667{col 37}{space 1}   -1.26{col 46}{space 3}0.209{col 54}{space 4}-.3616842{col 67}{space 3} .0790797
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .0061712{col 26}{space 2} .1498242{col 37}{space 1}    0.04{col 46}{space 3}0.967{col 54}{space 4}-.2879369{col 67}{space 3} .3002792
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .1250721{col 26}{space 2}  .157454{col 37}{space 1}    0.79{col 46}{space 3}0.427{col 54}{space 4}-.1840135{col 67}{space 3} .4341576
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0656971{col 26}{space 2} .1537639{col 37}{space 1}    0.43{col 46}{space 3}0.669{col 54}{space 4}-.2361448{col 67}{space 3} .3675389
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0911785{col 26}{space 2} .0991067{col 37}{space 1}   -0.92{col 46}{space 3}0.358{col 54}{space 4} -.285727{col 67}{space 3} .1033701
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0631883{col 26}{space 2} .0873558{col 37}{space 1}   -0.72{col 46}{space 3}0.470{col 54}{space 4}-.2346696{col 67}{space 3} .1082929
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2}-.0432661{col 26}{space 2} .1523571{col 37}{space 1}   -0.28{col 46}{space 3}0.777{col 54}{space 4}-.3423464{col 67}{space 3} .2558143
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.927992{col 26}{space 2} .1195757{col 37}{space 1}   32.85{col 46}{space 3}0.000{col 54}{space 4} 3.693262{col 67}{space 3} 4.162721
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof_rk", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 3)      label   
{txt}{stata `"shellout using `"Tables/rob_prof_rk.tex"'"':Tables/rob_prof_rk.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof_rk.txt", label"':seeout}

{com}.         reg rank elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profile==4, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    1556
                                                       {txt}F( 35,   777) ={res}   15.21
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.2022
                                                       {txt}Root MSE      = {res}  .7833

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2}  .160098{col 26}{space 2}  .040294{col 37}{space 1}    3.97{col 46}{space 3}0.000{col 54}{space 4}     .081{col 67}{space 3} .2391959
{txt}{space 7}local {c |}{col 14}{res}{space 2} .0032087{col 26}{space 2} .0403597{col 37}{space 1}    0.08{col 46}{space 3}0.937{col 54}{space 4}-.0760184{col 67}{space 3} .0824357
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2116966{col 26}{space 2} .0493766{col 37}{space 1}    4.29{col 46}{space 3}0.000{col 54}{space 4} .1147692{col 67}{space 3}  .308624
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0837606{col 26}{space 2} .0508691{col 37}{space 1}    1.65{col 46}{space 3}0.100{col 54}{space 4}-.0160966{col 67}{space 3} .1836178
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.3622113{col 26}{space 2} .0497899{col 37}{space 1}   -7.27{col 46}{space 3}0.000{col 54}{space 4}-.4599501{col 67}{space 3}-.2644726
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.2353839{col 26}{space 2} .0481218{col 37}{space 1}   -4.89{col 46}{space 3}0.000{col 54}{space 4} -.329848{col 67}{space 3}-.1409198
{txt}{space 7}water {c |}{col 14}{res}{space 2} .1022402{col 26}{space 2} .0695268{col 37}{space 1}    1.47{col 46}{space 3}0.142{col 54}{space 4}-.0342424{col 67}{space 3} .2387227
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4131458{col 26}{space 2} .0648146{col 37}{space 1}    6.37{col 46}{space 3}0.000{col 54}{space 4} .2859133{col 67}{space 3} .5403782
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .2093785{col 26}{space 2} .0660833{col 37}{space 1}    3.17{col 46}{space 3}0.002{col 54}{space 4} .0796556{col 67}{space 3} .3391014
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .1742317{col 26}{space 2} .0671456{col 37}{space 1}    2.59{col 46}{space 3}0.010{col 54}{space 4} .0424234{col 67}{space 3} .3060401
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .5653323{col 26}{space 2} .1511933{col 37}{space 1}    3.74{col 46}{space 3}0.000{col 54}{space 4} .2685366{col 67}{space 3} .8621281
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2} .1730198{col 26}{space 2}  .152958{col 37}{space 1}    1.13{col 46}{space 3}0.258{col 54}{space 4}  -.12724{col 67}{space 3} .4732796
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .1569941{col 26}{space 2}  .153144{col 37}{space 1}    1.03{col 46}{space 3}0.306{col 54}{space 4}-.1436309{col 67}{space 3} .4576191
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .4744549{col 26}{space 2} .1527233{col 37}{space 1}    3.11{col 46}{space 3}0.002{col 54}{space 4} .1746557{col 67}{space 3}  .774254
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .6456204{col 26}{space 2}  .083028{col 37}{space 1}    7.78{col 46}{space 3}0.000{col 54}{space 4} .4826346{col 67}{space 3} .8086063
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} -.034778{col 26}{space 2} .0914239{col 37}{space 1}   -0.38{col 46}{space 3}0.704{col 54}{space 4}-.2142451{col 67}{space 3} .1446892
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.2454583{col 26}{space 2} .0916698{col 37}{space 1}   -2.68{col 46}{space 3}0.008{col 54}{space 4}-.4254081{col 67}{space 3}-.0655085
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2}  .694412{col 26}{space 2} .0852541{col 37}{space 1}    8.15{col 46}{space 3}0.000{col 54}{space 4} .5270564{col 67}{space 3} .8617675
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .1801573{col 26}{space 2} .1521042{col 37}{space 1}    1.18{col 46}{space 3}0.237{col 54}{space 4}-.1184265{col 67}{space 3} .4787411
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.3695574{col 26}{space 2} .1329112{col 37}{space 1}   -2.78{col 46}{space 3}0.006{col 54}{space 4} -.630465{col 67}{space 3}-.1086499
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2}-.0527009{col 26}{space 2} .1294247{col 37}{space 1}   -0.41{col 46}{space 3}0.684{col 54}{space 4}-.3067643{col 67}{space 3} .2013626
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.3237881{col 26}{space 2} .1368515{col 37}{space 1}   -2.37{col 46}{space 3}0.018{col 54}{space 4}-.5924306{col 67}{space 3}-.0551456
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0956819{col 26}{space 2} .1090478{col 37}{space 1}   -0.88{col 46}{space 3}0.381{col 54}{space 4} -.309745{col 67}{space 3} .1183812
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} -.152991{col 26}{space 2} .1010316{col 37}{space 1}   -1.51{col 46}{space 3}0.130{col 54}{space 4}-.3513182{col 67}{space 3} .0453362
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.1667848{col 26}{space 2} .0938042{col 37}{space 1}   -1.78{col 46}{space 3}0.076{col 54}{space 4}-.3509244{col 67}{space 3} .0173548
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.0609601{col 26}{space 2} .1060586{col 37}{space 1}   -0.57{col 46}{space 3}0.566{col 54}{space 4}-.2691554{col 67}{space 3} .1472352
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.0685108{col 26}{space 2} .0953783{col 37}{space 1}   -0.72{col 46}{space 3}0.473{col 54}{space 4}-.2557404{col 67}{space 3} .1187188
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0925985{col 26}{space 2} .1365939{col 37}{space 1}   -0.68{col 46}{space 3}0.498{col 54}{space 4}-.3607353{col 67}{space 3} .1755383
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.2102633{col 26}{space 2} .1163056{col 37}{space 1}   -1.81{col 46}{space 3}0.071{col 54}{space 4}-.4385738{col 67}{space 3} .0180472
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}-.0491589{col 26}{space 2} .1299359{col 37}{space 1}   -0.38{col 46}{space 3}0.705{col 54}{space 4}-.3042258{col 67}{space 3}  .205908
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .1053464{col 26}{space 2} .1186676{col 37}{space 1}    0.89{col 46}{space 3}0.375{col 54}{space 4}-.1276008{col 67}{space 3} .3382935
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2}-.1467711{col 26}{space 2} .1364814{col 37}{space 1}   -1.08{col 46}{space 3}0.283{col 54}{space 4} -.414687{col 67}{space 3} .1211449
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} -.126172{col 26}{space 2} .1012232{col 37}{space 1}   -1.25{col 46}{space 3}0.213{col 54}{space 4}-.3248754{col 67}{space 3} .0725313
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0071154{col 26}{space 2} .1031639{col 37}{space 1}    0.07{col 46}{space 3}0.945{col 54}{space 4}-.1953977{col 67}{space 3} .2096284
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2}-.1174727{col 26}{space 2} .1312346{col 37}{space 1}   -0.90{col 46}{space 3}0.371{col 54}{space 4}-.3750891{col 67}{space 3} .1401438
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.825728{col 26}{space 2} .1164922{col 37}{space 1}   32.84{col 46}{space 3}0.000{col 54}{space 4} 3.597051{col 67}{space 3} 4.054404
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/rob_prof_rk", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof Pair 4)      label   
{txt}{stata `"shellout using `"Tables/rob_prof_rk.tex"'"':Tables/rob_prof_rk.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_prof_rk.txt", label"':seeout}

{com}. 
.                 
.                 
. // TABLE 6: OLS results for Chosen and Rank broken down by within-profile-pair order 
.         reg chosen elect local tax transfer kinvill buyel water health educ infra $fe  $townfe if profileab==1, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity

Linear regression                                      Number of obs ={res}    3112
                                                       {txt}F( 35,   777) ={res}   14.78
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1224
                                                       {txt}Root MSE      = {res} .47104

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1029739{col 26}{space 2} .0183879{col 37}{space 1}    5.60{col 46}{space 3}0.000{col 54}{space 4}  .066878{col 67}{space 3} .1390698
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0302071{col 26}{space 2} .0170773{col 37}{space 1}   -1.77{col 46}{space 3}0.077{col 54}{space 4}-.0637303{col 67}{space 3} .0033161
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2104844{col 26}{space 2} .0213427{col 37}{space 1}    9.86{col 46}{space 3}0.000{col 54}{space 4} .1685882{col 67}{space 3} .2523806
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0207724{col 26}{space 2} .0212893{col 37}{space 1}    0.98{col 46}{space 3}0.330{col 54}{space 4}-.0210189{col 67}{space 3} .0625638
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2} -.194235{col 26}{space 2} .0212334{col 37}{space 1}   -9.15{col 46}{space 3}0.000{col 54}{space 4}-.2359166{col 67}{space 3}-.1525533
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.1454487{col 26}{space 2}  .021519{col 37}{space 1}   -6.76{col 46}{space 3}0.000{col 54}{space 4} -.187691{col 67}{space 3}-.1032065
{txt}{space 7}water {c |}{col 14}{res}{space 2}  .103149{col 26}{space 2} .0271859{col 37}{space 1}    3.79{col 46}{space 3}0.000{col 54}{space 4} .0497826{col 67}{space 3} .1565155
{txt}{space 6}health {c |}{col 14}{res}{space 2} .2588242{col 26}{space 2} .0269069{col 37}{space 1}    9.62{col 46}{space 3}0.000{col 54}{space 4} .2060054{col 67}{space 3}  .311643
{txt}{space 8}educ {c |}{col 14}{res}{space 2}  .129884{col 26}{space 2} .0272441{col 37}{space 1}    4.77{col 46}{space 3}0.000{col 54}{space 4} .0764033{col 67}{space 3} .1833647
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .1020582{col 26}{space 2} .0278666{col 37}{space 1}    3.66{col 46}{space 3}0.000{col 54}{space 4} .0473555{col 67}{space 3} .1567609
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.0579111{col 26}{space 2} .0397437{col 37}{space 1}   -1.46{col 46}{space 3}0.145{col 54}{space 4}-.1359288{col 67}{space 3} .0201066
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.0300625{col 26}{space 2} .0383366{col 37}{space 1}   -0.78{col 46}{space 3}0.433{col 54}{space 4} -.105318{col 67}{space 3}  .045193
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2}-.0143945{col 26}{space 2} .0402599{col 37}{space 1}   -0.36{col 46}{space 3}0.721{col 54}{space 4}-.0934257{col 67}{space 3} .0646366
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0549259{col 26}{space 2} .0395344{col 37}{space 1}   -1.39{col 46}{space 3}0.165{col 54}{space 4}-.1325328{col 67}{space 3}  .022681
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} .0057445{col 26}{space 2} .0416857{col 37}{space 1}    0.14{col 46}{space 3}0.890{col 54}{space 4}-.0760855{col 67}{space 3} .0875744
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2} .0039357{col 26}{space 2} .0407272{col 37}{space 1}    0.10{col 46}{space 3}0.923{col 54}{space 4}-.0760127{col 67}{space 3} .0838841
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .1698264{col 26}{space 2} .0378457{col 37}{space 1}    4.49{col 46}{space 3}0.000{col 54}{space 4} .0955345{col 67}{space 3} .2441182
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.0547878{col 26}{space 2} .0385002{col 37}{space 1}   -1.42{col 46}{space 3}0.155{col 54}{space 4}-.1303646{col 67}{space 3} .0207889
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0577699{col 26}{space 2} .0614212{col 37}{space 1}    0.94{col 46}{space 3}0.347{col 54}{space 4}-.0628013{col 67}{space 3}  .178341
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0467425{col 26}{space 2} .0584705{col 37}{space 1}    0.80{col 46}{space 3}0.424{col 54}{space 4}-.0680364{col 67}{space 3} .1615213
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .0536708{col 26}{space 2} .0564412{col 37}{space 1}    0.95{col 46}{space 3}0.342{col 54}{space 4}-.0571245{col 67}{space 3} .1644662
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0046248{col 26}{space 2} .0761246{col 37}{space 1}   -0.06{col 46}{space 3}0.952{col 54}{space 4}-.1540591{col 67}{space 3} .1448094
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} .0462683{col 26}{space 2} .0714809{col 37}{space 1}    0.65{col 46}{space 3}0.518{col 54}{space 4}-.0940503{col 67}{space 3} .1865869
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.0913804{col 26}{space 2} .0742438{col 37}{space 1}   -1.23{col 46}{space 3}0.219{col 54}{space 4}-.2371227{col 67}{space 3} .0543618
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0331347{col 26}{space 2} .0734694{col 37}{space 1}    0.45{col 46}{space 3}0.652{col 54}{space 4}-.1110872{col 67}{space 3} .1773567
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0076257{col 26}{space 2} .0738532{col 37}{space 1}    0.10{col 46}{space 3}0.918{col 54}{space 4}-.1373498{col 67}{space 3} .1526012
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0002888{col 26}{space 2} .0590924{col 37}{space 1}   -0.00{col 46}{space 3}0.996{col 54}{space 4}-.1162885{col 67}{space 3} .1157109
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.0357953{col 26}{space 2} .0797357{col 37}{space 1}   -0.45{col 46}{space 3}0.654{col 54}{space 4}-.1923183{col 67}{space 3} .1207277
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .0222773{col 26}{space 2} .0583363{col 37}{space 1}    0.38{col 46}{space 3}0.703{col 54}{space 4}-.0922382{col 67}{space 3} .1367928
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .0511387{col 26}{space 2} .0598138{col 37}{space 1}    0.85{col 46}{space 3}0.393{col 54}{space 4}-.0662771{col 67}{space 3} .1685546
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0070149{col 26}{space 2} .0589595{col 37}{space 1}    0.12{col 46}{space 3}0.905{col 54}{space 4}-.1087238{col 67}{space 3} .1227536
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0474532{col 26}{space 2} .0743829{col 37}{space 1}   -0.64{col 46}{space 3}0.524{col 54}{space 4}-.1934684{col 67}{space 3} .0985621
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0160893{col 26}{space 2} .0742545{col 37}{space 1}   -0.22{col 46}{space 3}0.829{col 54}{space 4}-.1618525{col 67}{space 3} .1296739
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2} .0600202{col 26}{space 2}  .075731{col 37}{space 1}    0.79{col 46}{space 3}0.428{col 54}{space 4}-.0886415{col 67}{space 3} .2086819
{txt}{space 3}townfe_18 {c |}{col 14}{res}{space 2} .0181937{col 26}{space 2} .0613034{col 37}{space 1}    0.30{col 46}{space 3}0.767{col 54}{space 4}-.1021461{col 67}{space 3} .1385336
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3830623{col 26}{space 2} .0686509{col 37}{space 1}    5.58{col 46}{space 3}0.000{col 54}{space 4} .2482992{col 67}{space 3} .5178255
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                         outreg2 using "Tables/rob_ab", replace tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof A Chosen)        label   
{txt}{stata `"shellout using `"Tables/rob_ab.tex"'"':Tables/rob_ab.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_ab.txt", label"':seeout}

{com}.         reg chosen elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profileab==2, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity

Linear regression                                      Number of obs ={res}    3112
                                                       {txt}F( 35,   777) ={res}   13.71
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1067
                                                       {txt}Root MSE      = {res} .47523

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .0952337{col 26}{space 2} .0184246{col 37}{space 1}    5.17{col 46}{space 3}0.000{col 54}{space 4} .0590659{col 67}{space 3} .1314015
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0014833{col 26}{space 2} .0171817{col 37}{space 1}   -0.09{col 46}{space 3}0.931{col 54}{space 4}-.0352114{col 67}{space 3} .0322448
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .1961977{col 26}{space 2} .0219939{col 37}{space 1}    8.92{col 46}{space 3}0.000{col 54}{space 4} .1530231{col 67}{space 3} .2393722
{txt}{space 4}transfer {c |}{col 14}{res}{space 2}  .037912{col 26}{space 2} .0213552{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0040088{col 67}{space 3} .0798327
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.1968803{col 26}{space 2} .0213838{col 37}{space 1}   -9.21{col 46}{space 3}0.000{col 54}{space 4}-.2388573{col 67}{space 3}-.1549034
{txt}{space 7}buyel {c |}{col 14}{res}{space 2} -.142255{col 26}{space 2} .0215118{col 37}{space 1}   -6.61{col 46}{space 3}0.000{col 54}{space 4}-.1844832{col 67}{space 3}-.1000268
{txt}{space 7}water {c |}{col 14}{res}{space 2} .0626121{col 26}{space 2}  .027811{col 37}{space 1}    2.25{col 46}{space 3}0.025{col 54}{space 4} .0080185{col 67}{space 3} .1172058
{txt}{space 6}health {c |}{col 14}{res}{space 2} .2334373{col 26}{space 2} .0280463{col 37}{space 1}    8.32{col 46}{space 3}0.000{col 54}{space 4} .1783819{col 67}{space 3} .2884928
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .1337236{col 26}{space 2}  .026906{col 37}{space 1}    4.97{col 46}{space 3}0.000{col 54}{space 4} .0809064{col 67}{space 3} .1865407
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .0743891{col 26}{space 2} .0265122{col 37}{space 1}    2.81{col 46}{space 3}0.005{col 54}{space 4}  .022345{col 67}{space 3} .1264332
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .0355065{col 26}{space 2} .0409906{col 37}{space 1}    0.87{col 46}{space 3}0.387{col 54}{space 4} -.044959{col 67}{space 3} .1159719
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2} -.013092{col 26}{space 2} .0401107{col 37}{space 1}   -0.33{col 46}{space 3}0.744{col 54}{space 4}-.0918303{col 67}{space 3} .0656463
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2} .0115586{col 26}{space 2} .0424398{col 37}{space 1}    0.27{col 46}{space 3}0.785{col 54}{space 4}-.0717516{col 67}{space 3} .0948689
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}  .042631{col 26}{space 2} .0412758{col 37}{space 1}    1.03{col 46}{space 3}0.302{col 54}{space 4}-.0383943{col 67}{space 3} .1236563
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.0150649{col 26}{space 2} .0421651{col 37}{space 1}   -0.36{col 46}{space 3}0.721{col 54}{space 4} -.097836{col 67}{space 3} .0677062
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0157665{col 26}{space 2} .0414931{col 37}{space 1}   -0.38{col 46}{space 3}0.704{col 54}{space 4}-.0972183{col 67}{space 3} .0656854
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2}-.1669476{col 26}{space 2} .0383897{col 37}{space 1}   -4.35{col 46}{space 3}0.000{col 54}{space 4}-.2423074{col 67}{space 3}-.0915878
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .0453447{col 26}{space 2} .0409812{col 37}{space 1}    1.11{col 46}{space 3}0.269{col 54}{space 4}-.0351024{col 67}{space 3} .1257917
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.0671748{col 26}{space 2} .0582968{col 37}{space 1}   -1.15{col 46}{space 3}0.250{col 54}{space 4}-.1816127{col 67}{space 3} .0472631
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2}-.0042563{col 26}{space 2} .0548076{col 37}{space 1}   -0.08{col 46}{space 3}0.938{col 54}{space 4}-.1118448{col 67}{space 3} .1033323
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0521845{col 26}{space 2} .0544848{col 37}{space 1}   -0.96{col 46}{space 3}0.338{col 54}{space 4}-.1591394{col 67}{space 3} .0547704
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .0277823{col 26}{space 2} .0726934{col 37}{space 1}    0.38{col 46}{space 3}0.702{col 54}{space 4}-.1149164{col 67}{space 3} .1704811
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.0514558{col 26}{space 2} .0686225{col 37}{space 1}   -0.75{col 46}{space 3}0.454{col 54}{space 4}-.1861632{col 67}{space 3} .0832516
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2} .0962862{col 26}{space 2} .0714617{col 37}{space 1}    1.35{col 46}{space 3}0.178{col 54}{space 4}-.0439946{col 67}{space 3}  .236567
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.0016546{col 26}{space 2} .0733481{col 37}{space 1}   -0.02{col 46}{space 3}0.982{col 54}{space 4}-.1456384{col 67}{space 3} .1423293
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0041711{col 26}{space 2} .0733635{col 37}{space 1}    0.06{col 46}{space 3}0.955{col 54}{space 4}-.1398429{col 67}{space 3} .1481852
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}  .010596{col 26}{space 2} .0550831{col 37}{space 1}    0.19{col 46}{space 3}0.848{col 54}{space 4}-.0975333{col 67}{space 3} .1187254
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .0587053{col 26}{space 2} .0758164{col 37}{space 1}    0.77{col 46}{space 3}0.439{col 54}{space 4}-.0901241{col 67}{space 3} .2075346
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}-.0075818{col 26}{space 2} .0566746{col 37}{space 1}   -0.13{col 46}{space 3}0.894{col 54}{space 4}-.1188352{col 67}{space 3} .1036717
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2}-.0226145{col 26}{space 2} .0575538{col 37}{space 1}   -0.39{col 46}{space 3}0.694{col 54}{space 4}-.1355938{col 67}{space 3} .0903649
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0230627{col 26}{space 2}  .052926{col 37}{space 1}    0.44{col 46}{space 3}0.663{col 54}{space 4}-.0808322{col 67}{space 3} .1269576
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} .0430196{col 26}{space 2} .0728336{col 37}{space 1}    0.59{col 46}{space 3}0.555{col 54}{space 4}-.0999544{col 67}{space 3} .1859935
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0382171{col 26}{space 2} .0729974{col 37}{space 1}    0.52{col 46}{space 3}0.601{col 54}{space 4}-.1050784{col 67}{space 3} .1815127
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}-.0497784{col 26}{space 2} .0740877{col 37}{space 1}   -0.67{col 46}{space 3}0.502{col 54}{space 4}-.1952142{col 67}{space 3} .0956574
{txt}{space 3}townfe_18 {c |}{col 14}{res}{space 2}  .015793{col 26}{space 2}  .054914{col 37}{space 1}    0.29{col 46}{space 3}0.774{col 54}{space 4}-.0920044{col 67}{space 3} .1235904
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3856366{col 26}{space 2} .0629548{col 37}{space 1}    6.13{col 46}{space 3}0.000{col 54}{space 4} .2620549{col 67}{space 3} .5092182
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                         outreg2 using "Tables/rob_ab", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Prof B Chosen) label   
{txt}{stata `"shellout using `"Tables/rob_ab.tex"'"':Tables/rob_ab.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_ab.txt", label"':seeout}

{com}.         reg rank elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profileab==1, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity

Linear regression                                      Number of obs ={res}    3112
                                                       {txt}F( 35,   777) ={res}   24.32
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.2146
                                                       {txt}Root MSE      = {res} .78309

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1329109{col 26}{space 2} .0294519{col 37}{space 1}    4.51{col 46}{space 3}0.000{col 54}{space 4} .0750961{col 67}{space 3} .1907257
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0382547{col 26}{space 2} .0282668{col 37}{space 1}   -1.35{col 46}{space 3}0.176{col 54}{space 4}-.0937429{col 67}{space 3} .0172336
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .3034788{col 26}{space 2} .0365479{col 37}{space 1}    8.30{col 46}{space 3}0.000{col 54}{space 4} .2317345{col 67}{space 3}  .375223
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0712198{col 26}{space 2} .0356247{col 37}{space 1}    2.00{col 46}{space 3}0.046{col 54}{space 4} .0012877{col 67}{space 3} .1411518
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.3201964{col 26}{space 2} .0361052{col 37}{space 1}   -8.87{col 46}{space 3}0.000{col 54}{space 4}-.3910716{col 67}{space 3}-.2493212
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.1931285{col 26}{space 2} .0342834{col 37}{space 1}   -5.63{col 46}{space 3}0.000{col 54}{space 4}-.2604276{col 67}{space 3}-.1258294
{txt}{space 7}water {c |}{col 14}{res}{space 2} .2394386{col 26}{space 2} .0503863{col 37}{space 1}    4.75{col 46}{space 3}0.000{col 54}{space 4} .1405291{col 67}{space 3}  .338348
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4274101{col 26}{space 2}  .048338{col 37}{space 1}    8.84{col 46}{space 3}0.000{col 54}{space 4} .3325215{col 67}{space 3} .5222986
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .3330135{col 26}{space 2} .0486155{col 37}{space 1}    6.85{col 46}{space 3}0.000{col 54}{space 4} .2375801{col 67}{space 3} .4284468
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .2662386{col 26}{space 2} .0500602{col 37}{space 1}    5.32{col 46}{space 3}0.000{col 54}{space 4} .1679694{col 67}{space 3} .3645078
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .3417398{col 26}{space 2} .0759189{col 37}{space 1}    4.50{col 46}{space 3}0.000{col 54}{space 4} .1927094{col 67}{space 3} .4907702
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.2905809{col 26}{space 2} .0647075{col 37}{space 1}   -4.49{col 46}{space 3}0.000{col 54}{space 4}-.4176031{col 67}{space 3}-.1635587
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2} .2707901{col 26}{space 2} .0698194{col 37}{space 1}    3.88{col 46}{space 3}0.000{col 54}{space 4} .1337332{col 67}{space 3}  .407847
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .7354191{col 26}{space 2} .0771559{col 37}{space 1}    9.53{col 46}{space 3}0.000{col 54}{space 4} .5839604{col 67}{space 3} .8868778
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} .1264257{col 26}{space 2} .0838641{col 37}{space 1}    1.51{col 46}{space 3}0.132{col 54}{space 4}-.0382013{col 67}{space 3} .2910527
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.2094687{col 26}{space 2} .0900296{col 37}{space 1}   -2.33{col 46}{space 3}0.020{col 54}{space 4}-.3861989{col 67}{space 3}-.0327385
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .7472416{col 26}{space 2} .0749504{col 37}{space 1}    9.97{col 46}{space 3}0.000{col 54}{space 4} .6001123{col 67}{space 3} .8943709
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.0065099{col 26}{space 2} .0702942{col 37}{space 1}   -0.09{col 46}{space 3}0.926{col 54}{space 4}-.1444991{col 67}{space 3} .1314792
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.2217777{col 26}{space 2} .1062112{col 37}{space 1}   -2.09{col 46}{space 3}0.037{col 54}{space 4}-.4302725{col 67}{space 3}-.0132829
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2}-.0411511{col 26}{space 2}  .093393{col 37}{space 1}   -0.44{col 46}{space 3}0.660{col 54}{space 4}-.2244837{col 67}{space 3} .1421815
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0531481{col 26}{space 2} .0901325{col 37}{space 1}   -0.59{col 46}{space 3}0.556{col 54}{space 4}-.2300801{col 67}{space 3} .1237839
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.3716945{col 26}{space 2} .1415057{col 37}{space 1}   -2.63{col 46}{space 3}0.009{col 54}{space 4}-.6494733{col 67}{space 3}-.0939157
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.4009282{col 26}{space 2} .1288198{col 37}{space 1}   -3.11{col 46}{space 3}0.002{col 54}{space 4}-.6538043{col 67}{space 3}-.1480522
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.4683485{col 26}{space 2} .1388298{col 37}{space 1}   -3.37{col 46}{space 3}0.001{col 54}{space 4}-.7408745{col 67}{space 3}-.1958225
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.3569742{col 26}{space 2} .1315793{col 37}{space 1}   -2.71{col 46}{space 3}0.007{col 54}{space 4}-.6152672{col 67}{space 3}-.0986812
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.3047247{col 26}{space 2} .1292042{col 37}{space 1}   -2.36{col 46}{space 3}0.019{col 54}{space 4}-.5583553{col 67}{space 3} -.051094
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.2031464{col 26}{space 2} .1006742{col 37}{space 1}   -2.02{col 46}{space 3}0.044{col 54}{space 4} -.400772{col 67}{space 3}-.0055208
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.3647048{col 26}{space 2} .1300828{col 37}{space 1}   -2.80{col 46}{space 3}0.005{col 54}{space 4}-.6200602{col 67}{space 3}-.1093493
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}-.0475897{col 26}{space 2} .0966726{col 37}{space 1}   -0.49{col 46}{space 3}0.623{col 54}{space 4}-.2373601{col 67}{space 3} .1421807
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2}-.0009589{col 26}{space 2} .0887712{col 37}{space 1}   -0.01{col 46}{space 3}0.991{col 54}{space 4}-.1752188{col 67}{space 3} .1733009
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2}-.2076875{col 26}{space 2} .1076109{col 37}{space 1}   -1.93{col 46}{space 3}0.054{col 54}{space 4}-.4189301{col 67}{space 3}  .003555
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} -.357121{col 26}{space 2} .1290415{col 37}{space 1}   -2.77{col 46}{space 3}0.006{col 54}{space 4}-.6104323{col 67}{space 3}-.1038097
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.2496679{col 26}{space 2} .1264772{col 37}{space 1}   -1.97{col 46}{space 3}0.049{col 54}{space 4}-.4979454{col 67}{space 3}-.0013904
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2} -.223834{col 26}{space 2} .1270003{col 37}{space 1}   -1.76{col 46}{space 3}0.078{col 54}{space 4}-.4731384{col 67}{space 3} .0254703
{txt}{space 3}townfe_18 {c |}{col 14}{res}{space 2}-.2026045{col 26}{space 2} .1050017{col 37}{space 1}   -1.93{col 46}{space 3}0.054{col 54}{space 4}-.4087251{col 67}{space 3} .0035162
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  3.86976{col 26}{space 2} .1092201{col 37}{space 1}   35.43{col 46}{space 3}0.000{col 54}{space 4} 3.655359{col 67}{space 3} 4.084162
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                         outreg2 using "Tables/rob_ab", append tex(frag) bdec(3) drop(e_*  $townfe) ctitle(Prof A Rank)  label   
{txt}{stata `"shellout using `"Tables/rob_ab.tex"'"':Tables/rob_ab.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_ab.txt", label"':seeout}

{com}.         reg rank elect local tax transfer kinvill buyel water health educ infra $fe $townfe if profileab==2, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity

Linear regression                                      Number of obs ={res}    3112
                                                       {txt}F( 35,   777) ={res}   23.04
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1945
                                                       {txt}Root MSE      = {res}  .8329

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1270076{col 26}{space 2} .0316286{col 37}{space 1}    4.02{col 46}{space 3}0.000{col 54}{space 4}   .06492{col 67}{space 3} .1890952
{txt}{space 7}local {c |}{col 14}{res}{space 2}  .008336{col 26}{space 2} .0299606{col 37}{space 1}    0.28{col 46}{space 3}0.781{col 54}{space 4}-.0504773{col 67}{space 3} .0671493
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .2997457{col 26}{space 2} .0392985{col 37}{space 1}    7.63{col 46}{space 3}0.000{col 54}{space 4} .2226018{col 67}{space 3} .3768896
{txt}{space 4}transfer {c |}{col 14}{res}{space 2}  .069981{col 26}{space 2} .0379878{col 37}{space 1}    1.84{col 46}{space 3}0.066{col 54}{space 4}-.0045898{col 67}{space 3} .1445518
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.3316455{col 26}{space 2}  .037729{col 37}{space 1}   -8.79{col 46}{space 3}0.000{col 54}{space 4}-.4057083{col 67}{space 3}-.2575828
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.2340771{col 26}{space 2} .0356346{col 37}{space 1}   -6.57{col 46}{space 3}0.000{col 54}{space 4}-.3040287{col 67}{space 3}-.1641255
{txt}{space 7}water {c |}{col 14}{res}{space 2} .1140792{col 26}{space 2} .0530758{col 37}{space 1}    2.15{col 46}{space 3}0.032{col 54}{space 4} .0098902{col 67}{space 3} .2182682
{txt}{space 6}health {c |}{col 14}{res}{space 2} .4602459{col 26}{space 2} .0484131{col 37}{space 1}    9.51{col 46}{space 3}0.000{col 54}{space 4} .3652099{col 67}{space 3}  .555282
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .2645718{col 26}{space 2} .0488437{col 37}{space 1}    5.42{col 46}{space 3}0.000{col 54}{space 4} .1686906{col 67}{space 3} .3604531
{txt}{space 7}infra {c |}{col 14}{res}{space 2}  .190111{col 26}{space 2} .0494941{col 37}{space 1}    3.84{col 46}{space 3}0.000{col 54}{space 4}  .092953{col 67}{space 3} .2872689
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}  .153068{col 26}{space 2} .0763537{col 37}{space 1}    2.00{col 46}{space 3}0.045{col 54}{space 4}  .003184{col 67}{space 3}  .302952
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_3 {c |}{col 14}{res}{space 2}-.3261782{col 26}{space 2} .0699089{col 37}{space 1}   -4.67{col 46}{space 3}0.000{col 54}{space 4} -.463411{col 67}{space 3}-.1889454
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2} .1124922{col 26}{space 2} .0701205{col 37}{space 1}    1.60{col 46}{space 3}0.109{col 54}{space 4}-.0251559{col 67}{space 3} .2501404
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .6907397{col 26}{space 2} .0816923{col 37}{space 1}    8.46{col 46}{space 3}0.000{col 54}{space 4} .5303759{col 67}{space 3} .8511035
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.0908358{col 26}{space 2} .0862816{col 37}{space 1}   -1.05{col 46}{space 3}0.293{col 54}{space 4}-.2602086{col 67}{space 3} .0785369
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.1521324{col 26}{space 2} .0805124{col 37}{space 1}   -1.89{col 46}{space 3}0.059{col 54}{space 4}-.3101799{col 67}{space 3} .0059152
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .6672697{col 26}{space 2} .0771494{col 37}{space 1}    8.65{col 46}{space 3}0.000{col 54}{space 4} .5158239{col 67}{space 3} .8187156
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.1695225{col 26}{space 2} .0758028{col 37}{space 1}   -2.24{col 46}{space 3}0.026{col 54}{space 4} -.318325{col 67}{space 3}-.0207201
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .0139726{col 26}{space 2} .1508194{col 37}{space 1}    0.09{col 46}{space 3}0.926{col 54}{space 4}-.2820892{col 67}{space 3} .3100344
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .1272663{col 26}{space 2} .1443736{col 37}{space 1}    0.88{col 46}{space 3}0.378{col 54}{space 4}-.1561422{col 67}{space 3} .4106749
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0668622{col 26}{space 2} .1481211{col 37}{space 1}   -0.45{col 46}{space 3}0.652{col 54}{space 4}-.3576272{col 67}{space 3} .2239029
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.1699263{col 26}{space 2} .1703538{col 37}{space 1}   -1.00{col 46}{space 3}0.319{col 54}{space 4}-.5043346{col 67}{space 3} .1644819
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.2776513{col 26}{space 2} .1663568{col 37}{space 1}   -1.67{col 46}{space 3}0.096{col 54}{space 4}-.6042133{col 67}{space 3} .0489107
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2} -.087462{col 26}{space 2} .1655381{col 37}{space 1}   -0.53{col 46}{space 3}0.597{col 54}{space 4}-.4124169{col 67}{space 3} .2374928
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.1200772{col 26}{space 2}  .174191{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.4620179{col 67}{space 3} .2218635
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.1321252{col 26}{space 2} .1622979{col 37}{space 1}   -0.81{col 46}{space 3}0.416{col 54}{space 4}-.4507196{col 67}{space 3} .1864691
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .1538687{col 26}{space 2} .1495689{col 37}{space 1}    1.03{col 46}{space 3}0.304{col 54}{space 4}-.1397384{col 67}{space 3} .4474757
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} -.083604{col 26}{space 2} .1768826{col 37}{space 1}   -0.47{col 46}{space 3}0.637{col 54}{space 4}-.4308285{col 67}{space 3} .2636205
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .2582857{col 26}{space 2} .1428425{col 37}{space 1}    1.81{col 46}{space 3}0.071{col 54}{space 4}-.0221173{col 67}{space 3} .5386887
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .2877757{col 26}{space 2} .1476152{col 37}{space 1}    1.95{col 46}{space 3}0.052{col 54}{space 4}-.0019961{col 67}{space 3} .5775475
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2}  .273682{col 26}{space 2}  .142451{col 37}{space 1}    1.92{col 46}{space 3}0.055{col 54}{space 4}-.0059524{col 67}{space 3} .5533163
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0121915{col 26}{space 2} .1660454{col 37}{space 1}   -0.07{col 46}{space 3}0.941{col 54}{space 4}-.3381423{col 67}{space 3} .3137593
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0345342{col 26}{space 2} .1633612{col 37}{space 1}   -0.21{col 46}{space 3}0.833{col 54}{space 4}-.3552157{col 67}{space 3} .2861473
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}-.0039405{col 26}{space 2} .1696341{col 37}{space 1}   -0.02{col 46}{space 3}0.981{col 54}{space 4}-.3369358{col 67}{space 3} .3290549
{txt}{space 3}townfe_18 {c |}{col 14}{res}{space 2} .2522331{col 26}{space 2} .1377588{col 37}{space 1}    1.83{col 46}{space 3}0.067{col 54}{space 4}-.0181903{col 67}{space 3} .5226566
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.744153{col 26}{space 2} .1506598{col 37}{space 1}   24.85{col 46}{space 3}0.000{col 54}{space 4} 3.448405{col 67}{space 3} 4.039902
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                         outreg2 using "Tables/rob_ab", append tex(frag) bdec(3) drop(e_*  $townfe) ctitle(Prof B Rank)  label   
{txt}{stata `"shellout using `"Tables/rob_ab.tex"'"':Tables/rob_ab.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/rob_ab.txt", label"':seeout}

{com}. 
.                         
.                         
. // TABLE 7: Results using Probit (binary outcome) and ordered probit (5-pt ranking) instead of OLS.             
.         probit chosen elect local tax transfer kinvill buyel water health educ infra  $fe $townfe, cluster(pid)

{txt}note: e_10 omitted because of collinearity
note: townfe_17 omitted because of collinearity
note: townfe_18 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-4314.1481}  
Iteration 1:{space 3}log pseudolikelihood = {res:-4004.6273}  
Iteration 2:{space 3}log pseudolikelihood = {res:-4003.9027}  
Iteration 3:{space 3}log pseudolikelihood = {res:-4003.9027}  
{res}
{txt}Probit regression{col 51}Number of obs{col 67}= {res}      6224
{txt}{col 51}Wald chi2({res}35{txt}){col 67}= {res}    582.25
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-4003.9027{txt}{col 51}Pseudo R2{col 67}= {res}    0.0719

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      chosen{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .2660478{col 26}{space 2} .0372554{col 37}{space 1}    7.14{col 46}{space 3}0.000{col 54}{space 4} .1930285{col 67}{space 3} .3390671
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0421353{col 26}{space 2} .0338917{col 37}{space 1}   -1.24{col 46}{space 3}0.214{col 54}{space 4}-.1085617{col 67}{space 3} .0242912
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .5561741{col 26}{space 2} .0444251{col 37}{space 1}   12.52{col 46}{space 3}0.000{col 54}{space 4} .4691026{col 67}{space 3} .6432457
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0836572{col 26}{space 2} .0427807{col 37}{space 1}    1.96{col 46}{space 3}0.051{col 54}{space 4}-.0001915{col 67}{space 3} .1675059
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.5292726{col 26}{space 2} .0419795{col 37}{space 1}  -12.61{col 46}{space 3}0.000{col 54}{space 4} -.611551{col 67}{space 3}-.4469942
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.3870167{col 26}{space 2} .0425404{col 37}{space 1}   -9.10{col 46}{space 3}0.000{col 54}{space 4}-.4703944{col 67}{space 3}-.3036391
{txt}{space 7}water {c |}{col 14}{res}{space 2} .2260947{col 26}{space 2} .0561886{col 37}{space 1}    4.02{col 46}{space 3}0.000{col 54}{space 4}  .115967{col 67}{space 3} .3362224
{txt}{space 6}health {c |}{col 14}{res}{space 2} .6671785{col 26}{space 2} .0561474{col 37}{space 1}   11.88{col 46}{space 3}0.000{col 54}{space 4} .5571317{col 67}{space 3} .7772253
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .3575917{col 26}{space 2} .0536114{col 37}{space 1}    6.67{col 46}{space 3}0.000{col 54}{space 4} .2525154{col 67}{space 3} .4626681
{txt}{space 7}infra {c |}{col 14}{res}{space 2}  .237464{col 26}{space 2} .0541791{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 54}{space 4}  .131275{col 67}{space 3}  .343653
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.0173586{col 26}{space 2} .0222551{col 37}{space 1}   -0.78{col 46}{space 3}0.435{col 54}{space 4}-.0609779{col 67}{space 3} .0262606
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.0155105{col 26}{space 2} .0406105{col 37}{space 1}   -0.38{col 46}{space 3}0.703{col 54}{space 4}-.0951055{col 67}{space 3} .0640846
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2}-.0453554{col 26}{space 2} .0228648{col 37}{space 1}   -1.98{col 46}{space 3}0.047{col 54}{space 4}-.0901696{col 67}{space 3}-.0005412
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2} .0118355{col 26}{space 2} .0276673{col 37}{space 1}    0.43{col 46}{space 3}0.669{col 54}{space 4}-.0423913{col 67}{space 3} .0660624
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .0109064{col 26}{space 2} .0230431{col 37}{space 1}    0.47{col 46}{space 3}0.636{col 54}{space 4}-.0342573{col 67}{space 3} .0560701
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0320529{col 26}{space 2}  .038479{col 37}{space 1}   -0.83{col 46}{space 3}0.405{col 54}{space 4}-.1074704{col 67}{space 3} .0433646
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} -.028303{col 26}{space 2} .0397303{col 37}{space 1}   -0.71{col 46}{space 3}0.476{col 54}{space 4} -.106173{col 67}{space 3} .0495671
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.0310642{col 26}{space 2} .0399604{col 37}{space 1}   -0.78{col 46}{space 3}0.437{col 54}{space 4}-.1093852{col 67}{space 3} .0472568
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2}-.0101613{col 26}{space 2} .0399544{col 37}{space 1}   -0.25{col 46}{space 3}0.799{col 54}{space 4}-.0884705{col 67}{space 3} .0681478
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_1 {c |}{col 14}{res}{space 2}-.0529533{col 26}{space 2} .0330686{col 37}{space 1}   -1.60{col 46}{space 3}0.109{col 54}{space 4}-.1177667{col 67}{space 3}   .01186
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .0193928{col 26}{space 2} .0333341{col 37}{space 1}    0.58{col 46}{space 3}0.561{col 54}{space 4}-.0459408{col 67}{space 3} .0847263
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.0388429{col 26}{space 2} .0305089{col 37}{space 1}   -1.27{col 46}{space 3}0.203{col 54}{space 4}-.0986393{col 67}{space 3} .0209534
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .0202535{col 26}{space 2} .0328199{col 37}{space 1}    0.62{col 46}{space 3}0.537{col 54}{space 4}-.0440723{col 67}{space 3} .0845794
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}-.0438285{col 26}{space 2} .0391369{col 37}{space 1}   -1.12{col 46}{space 3}0.263{col 54}{space 4}-.1205353{col 67}{space 3} .0328783
{txt}{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.0174708{col 26}{space 2}  .033619{col 37}{space 1}   -0.52{col 46}{space 3}0.603{col 54}{space 4}-.0833629{col 67}{space 3} .0484212
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.0103893{col 26}{space 2}  .032805{col 37}{space 1}   -0.32{col 46}{space 3}0.751{col 54}{space 4}-.0746858{col 67}{space 3} .0539073
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0288162{col 26}{space 2} .0328808{col 37}{space 1}    0.88{col 46}{space 3}0.381{col 54}{space 4}-.0356289{col 67}{space 3} .0932614
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2} .0027735{col 26}{space 2} .0351926{col 37}{space 1}    0.08{col 46}{space 3}0.937{col 54}{space 4}-.0662027{col 67}{space 3} .0717497
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0234884{col 26}{space 2} .0309934{col 37}{space 1}   -0.76{col 46}{space 3}0.449{col 54}{space 4}-.0842344{col 67}{space 3} .0372575
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}   .01898{col 26}{space 2} .0371205{col 37}{space 1}    0.51{col 46}{space 3}0.609{col 54}{space 4}-.0537749{col 67}{space 3} .0917349
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}-.0186543{col 26}{space 2} .0328427{col 37}{space 1}   -0.57{col 46}{space 3}0.570{col 54}{space 4}-.0830247{col 67}{space 3} .0457162
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .0014023{col 26}{space 2} .0331446{col 37}{space 1}    0.04{col 46}{space 3}0.966{col 54}{space 4}  -.06356{col 67}{space 3} .0663645
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0014315{col 26}{space 2} .0304015{col 37}{space 1}    0.05{col 46}{space 3}0.962{col 54}{space 4}-.0581543{col 67}{space 3} .0610173
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0174901{col 26}{space 2} .0337851{col 37}{space 1}   -0.52{col 46}{space 3}0.605{col 54}{space 4}-.0837077{col 67}{space 3} .0487276
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0098145{col 26}{space 2} .0344492{col 37}{space 1}    0.28{col 46}{space 3}0.776{col 54}{space 4}-.0577047{col 67}{space 3} .0773337
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 7}_cons {c |}{col 14}{res}{space 2}-.2859423{col 26}{space 2} .0631112{col 37}{space 1}   -4.53{col 46}{space 3}0.000{col 54}{space 4}-.4096381{col 67}{space 3}-.1622466
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 outreg2 using "Tables/robust_probit", replace tex(frag) bdec(3) drop(e_* $townfe) ctitle(Chosen)        label   
{txt}{stata `"shellout using `"Tables/robust_probit.tex"'"':Tables/robust_probit.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/robust_probit.txt", label"':seeout}

{com}.         oprobit rank elect local tax transfer kinvill buyel water health educ infra  $fe, cluster(pid)

{txt}note: e_10 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-7616.2193}  
Iteration 1:{space 3}log pseudolikelihood = {res: -6959.126}  
Iteration 2:{space 3}log pseudolikelihood = {res:-6956.4957}  
Iteration 3:{space 3}log pseudolikelihood = {res:-6956.4952}  
{res}
{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      6224
{txt}{col 51}Wald chi2({res}19{txt}){col 67}= {res}   1121.39
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-6956.4952{txt}{col 51}Pseudo R2{col 67}= {res}    0.0866

{txt}{ralign 78:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        rank{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}elect {c |}{col 14}{res}{space 2} .1699474{col 26}{space 2}  .031205{col 37}{space 1}    5.45{col 46}{space 3}0.000{col 54}{space 4} .1087868{col 67}{space 3}  .231108
{txt}{space 7}local {c |}{col 14}{res}{space 2}-.0199989{col 26}{space 2} .0290085{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.0768545{col 67}{space 3} .0368567
{txt}{space 9}tax {c |}{col 14}{res}{space 2} .4048191{col 26}{space 2} .0401332{col 37}{space 1}   10.09{col 46}{space 3}0.000{col 54}{space 4} .3261595{col 67}{space 3} .4834787
{txt}{space 4}transfer {c |}{col 14}{res}{space 2} .0870428{col 26}{space 2} .0363523{col 37}{space 1}    2.39{col 46}{space 3}0.017{col 54}{space 4} .0157935{col 67}{space 3} .1582921
{txt}{space 5}kinvill {c |}{col 14}{res}{space 2}-.4517035{col 26}{space 2} .0380616{col 37}{space 1}  -11.87{col 46}{space 3}0.000{col 54}{space 4}-.5263029{col 67}{space 3}-.3771041
{txt}{space 7}buyel {c |}{col 14}{res}{space 2}-.3072235{col 26}{space 2} .0362111{col 37}{space 1}   -8.48{col 46}{space 3}0.000{col 54}{space 4} -.378196{col 67}{space 3} -.236251
{txt}{space 7}water {c |}{col 14}{res}{space 2} .2397003{col 26}{space 2}  .051311{col 37}{space 1}    4.67{col 46}{space 3}0.000{col 54}{space 4} .1391325{col 67}{space 3}  .340268
{txt}{space 6}health {c |}{col 14}{res}{space 2} .6085499{col 26}{space 2} .0521812{col 37}{space 1}   11.66{col 46}{space 3}0.000{col 54}{space 4} .5062765{col 67}{space 3} .7108232
{txt}{space 8}educ {c |}{col 14}{res}{space 2} .3968867{col 26}{space 2} .0493841{col 37}{space 1}    8.04{col 46}{space 3}0.000{col 54}{space 4} .3000957{col 67}{space 3} .4936777
{txt}{space 7}infra {c |}{col 14}{res}{space 2} .2977026{col 26}{space 2} .0488455{col 37}{space 1}    6.09{col 46}{space 3}0.000{col 54}{space 4} .2019671{col 67}{space 3}  .393438
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .5127655{col 26}{space 2} .0793188{col 37}{space 1}    6.46{col 46}{space 3}0.000{col 54}{space 4} .3573035{col 67}{space 3} .6682274
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.2117913{col 26}{space 2} .0835598{col 37}{space 1}   -2.53{col 46}{space 3}0.011{col 54}{space 4}-.3755655{col 67}{space 3}-.0480171
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2}-.2681331{col 26}{space 2}  .060233{col 37}{space 1}   -4.45{col 46}{space 3}0.000{col 54}{space 4}-.3861875{col 67}{space 3}-.1500787
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}  .144404{col 26}{space 2} .0599254{col 37}{space 1}    2.41{col 46}{space 3}0.016{col 54}{space 4} .0269524{col 67}{space 3} .2618557
{txt}{space 9}e_5 {c |}{col 14}{res}{space 2} .4169158{col 26}{space 2} .0631059{col 37}{space 1}    6.61{col 46}{space 3}0.000{col 54}{space 4} .2932305{col 67}{space 3} .5406011
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .8175341{col 26}{space 2} .0739966{col 37}{space 1}   11.05{col 46}{space 3}0.000{col 54}{space 4} .6725035{col 67}{space 3} .9625647
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} -.177472{col 26}{space 2} .0632787{col 37}{space 1}   -2.80{col 46}{space 3}0.005{col 54}{space 4} -.301496{col 67}{space 3}-.0534479
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.4060941{col 26}{space 2} .0545585{col 37}{space 1}   -7.44{col 46}{space 3}0.000{col 54}{space 4}-.5130268{col 67}{space 3}-.2991615
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .7618424{col 26}{space 2} .0680438{col 37}{space 1}   11.20{col 46}{space 3}0.000{col 54}{space 4} .6284791{col 67}{space 3} .8952058
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2}-2.927037{col 26}{space 2} .1644697{col 54}{space 4}-3.249392{col 67}{space 3}-2.604682
{txt}       /cut2 {c |}{col 14}{res}{space 2}-1.301087{col 26}{space 2} .0717305{col 54}{space 4}-1.441676{col 67}{space 3}-1.160498
{txt}       /cut3 {c |}{col 14}{res}{space 2}-.3124139{col 26}{space 2} .0699643{col 54}{space 4}-.4495414{col 67}{space 3}-.1752864
{txt}       /cut4 {c |}{col 14}{res}{space 2} .8039631{col 26}{space 2} .0711465{col 54}{space 4} .6645184{col 67}{space 3} .9434077
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 outreg2 using "Tables/robust_probit", append tex(frag) bdec(3) drop(e_* $townfe) ctitle(Rank)   label   
{txt}{stata `"shellout using `"Tables/robust_probit.tex"'"':Tables/robust_probit.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/robust_probit.txt", label"':seeout}

{com}. 
.                 
. ********        APPENDIX C4: CORRUPTION SEVERITY AND POLITICAL ACTION
. 
. * Open respondent-level dataset
.         use "respondent_level_clean.dta", clear
{txt}
{com}. 
.         * Set globals for analysis: enumerator fixed effects and town fixed effects
.                 gl fe "e_* "
{txt}
{com}.                 gl townfe "townfe_*"
{txt}
{com}. 
.         
.         
. // FIGURE 4: Collapse into averages, graph figure 4, restore full dataset
.         preserve
{txt}
{com}.         collapse (mean) talkneighb* contact_official* goprotest* campaign_*, by(steal_upset)
{txt}
{com}.         twoway (line goprotest steal_upset) (line talkneighb steal_upset, lpattern(dash)) (line campaign_against steal_upset, lpattern(dot)) (line contact_official steal_upset, lpattern(longdash)), legend(label(1 "Go to protest") label(2 "Talk to Neighbor") label(3 "Campaign against official") label(4 "Contact gov't official")) xtitle("Upset about scandal") ytitle("Likelihood of taking action") yscale(range(1 4)) ylabel(1(1)4)
{res}{txt}
{com}.         graph export "Tables/willact.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/willact.pdf written in PDF format)

{com}.         restore 
{txt}
{com}. 
.         
.         
. // TABLE 8: Relationship between a respondent�s evaluation of how upset they would be about a corruption scandal and the self-reported likelihood of taking part in each potential action
.         reg talkneighb steal_upset $fe $townfe
{txt}note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

      Source {c |}       SS       df       MS              Number of obs ={res}     778
{txt}{hline 13}{char +}{hline 30}           F( 26,   751) ={res}   14.84
    {txt}   Model {char |} {res} 319.256405    26  12.2790925           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 621.386269   751  .827411809           {txt}R-squared     = {res} 0.3394
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.3165
    {txt}   Total {char |} {res} 940.642674   777  1.21060833           {txt}Root MSE      = {res} .90962

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  talkneighb{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}steal_upset {c |}{col 14}{res}{space 2} .4141275{col 26}{space 2}  .042342{col 37}{space 1}    9.78{col 46}{space 3}0.000{col 54}{space 4} .3310048{col 67}{space 3} .4972502
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .1401748{col 26}{space 2} .1584501{col 37}{space 1}    0.88{col 46}{space 3}0.377{col 54}{space 4}-.1708831{col 67}{space 3} .4512327
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.1754369{col 26}{space 2} .2971162{col 37}{space 1}   -0.59{col 46}{space 3}0.555{col 54}{space 4} -.758714{col 67}{space 3} .4078403
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2} .0873701{col 26}{space 2} .1578812{col 37}{space 1}    0.55{col 46}{space 3}0.580{col 54}{space 4}-.2225708{col 67}{space 3}  .397311
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2} -.495357{col 26}{space 2} .1653869{col 37}{space 1}   -3.00{col 46}{space 3}0.003{col 54}{space 4}-.8200327{col 67}{space 3}-.1706814
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.2082801{col 26}{space 2} .2879507{col 37}{space 1}   -0.72{col 46}{space 3}0.470{col 54}{space 4}-.7735641{col 67}{space 3} .3570039
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} .3068599{col 26}{space 2} .2897248{col 37}{space 1}    1.06{col 46}{space 3}0.290{col 54}{space 4}-.2619068{col 67}{space 3} .8756267
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.6858371{col 26}{space 2} .2910609{col 37}{space 1}   -2.36{col 46}{space 3}0.019{col 54}{space 4}-1.257227{col 67}{space 3}-.1144473
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .7659087{col 26}{space 2} .2889503{col 37}{space 1}    2.65{col 46}{space 3}0.008{col 54}{space 4} .1986623{col 67}{space 3} 1.333155
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.1636686{col 26}{space 2} .1586685{col 37}{space 1}   -1.03{col 46}{space 3}0.303{col 54}{space 4}-.4751552{col 67}{space 3} .1478179
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .3788241{col 26}{space 2} .2284001{col 37}{space 1}    1.66{col 46}{space 3}0.098{col 54}{space 4}-.0695544{col 67}{space 3} .8272026
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .4351929{col 26}{space 2} .2310122{col 37}{space 1}    1.88{col 46}{space 3}0.060{col 54}{space 4}-.0183136{col 67}{space 3} .8886994
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2}-.1371986{col 26}{space 2} .2309474{col 37}{space 1}   -0.59{col 46}{space 3}0.553{col 54}{space 4}-.5905778{col 67}{space 3} .3161806
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2} .1361609{col 26}{space 2} .2034541{col 37}{space 1}    0.67{col 46}{space 3}0.504{col 54}{space 4}-.2632456{col 67}{space 3} .5355674
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} .1828522{col 26}{space 2} .2034323{col 37}{space 1}    0.90{col 46}{space 3}0.369{col 54}{space 4}-.2165115{col 67}{space 3} .5822159
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.2187379{col 26}{space 2} .2025302{col 37}{space 1}   -1.08{col 46}{space 3}0.280{col 54}{space 4}-.6163305{col 67}{space 3} .1788547
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2}-.0149562{col 26}{space 2} .2027084{col 37}{space 1}   -0.07{col 46}{space 3}0.941{col 54}{space 4}-.4128987{col 67}{space 3} .3829863
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.0538276{col 26}{space 2} .2025099{col 37}{space 1}   -0.27{col 46}{space 3}0.790{col 54}{space 4}-.4513805{col 67}{space 3} .3437252
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .6401125{col 26}{space 2} .2324009{col 37}{space 1}    2.75{col 46}{space 3}0.006{col 54}{space 4} .1838798{col 67}{space 3} 1.096345
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.2251308{col 26}{space 2} .2117207{col 37}{space 1}   -1.06{col 46}{space 3}0.288{col 54}{space 4}-.6407656{col 67}{space 3} .1905039
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .6424283{col 26}{space 2}  .226996{col 37}{space 1}    2.83{col 46}{space 3}0.005{col 54}{space 4} .1968061{col 67}{space 3}  1.08805
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .7424875{col 26}{space 2} .2309652{col 37}{space 1}    3.21{col 46}{space 3}0.001{col 54}{space 4} .2890733{col 67}{space 3} 1.195902
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .5004305{col 26}{space 2} .2316242{col 37}{space 1}    2.16{col 46}{space 3}0.031{col 54}{space 4} .0457226{col 67}{space 3} .9551384
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.0261689{col 26}{space 2} .2057277{col 37}{space 1}   -0.13{col 46}{space 3}0.899{col 54}{space 4}-.4300387{col 67}{space 3} .3777009
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .1191126{col 26}{space 2} .2044886{col 37}{space 1}    0.58{col 46}{space 3}0.560{col 54}{space 4}-.2823246{col 67}{space 3} .5205499
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .6758208{col 26}{space 2} .2309652{col 37}{space 1}    2.93{col 46}{space 3}0.004{col 54}{space 4} .2224066{col 67}{space 3} 1.129235
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  1.12224{col 26}{space 2} .2940369{col 37}{space 1}    3.82{col 46}{space 3}0.000{col 54}{space 4} .5450076{col 67}{space 3} 1.699472
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/will_act", replace tex(frag) bdec(3) drop($fe $townfe) ctitle(`x')
{txt}{stata `"shellout using `"Tables/will_act.tex"'"':Tables/will_act.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/will_act.txt""':seeout}

{com}.         foreach x of varlist contact_official goprotest campaign_against {c -(}
{txt}  2{com}.                 reg `x' steal_upset  $fe $townfe
{txt}  3{com}.                 outreg2 using "Tables/will_act", append tex(frag) bdec(3) drop($fe $townfe) ctitle(`x')
{txt}  4{com}.                 {c )-}
{txt}note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

      Source {c |}       SS       df       MS              Number of obs ={res}     778
{txt}{hline 13}{char +}{hline 30}           F( 26,   751) ={res}   22.13
    {txt}   Model {char |} {res} 516.742101    26  19.8746962           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 674.604943   751  .898275557           {txt}R-squared     = {res} 0.4337
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.4141
    {txt}   Total {char |} {res} 1191.34704   777  1.53326518           {txt}Root MSE      = {res} .94777

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}contact_of~l{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}steal_upset {c |}{col 14}{res}{space 2} .3795634{col 26}{space 2} .0441179{col 37}{space 1}    8.60{col 46}{space 3}0.000{col 54}{space 4} .2929542{col 67}{space 3} .4661725
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} -.845241{col 26}{space 2}  .165096{col 37}{space 1}   -5.12{col 46}{space 3}0.000{col 54}{space 4}-1.169346{col 67}{space 3}-.5211365
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.0332096{col 26}{space 2} .3095782{col 37}{space 1}   -0.11{col 46}{space 3}0.915{col 54}{space 4}-.6409511{col 67}{space 3} .5745319
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2}-.3396833{col 26}{space 2} .1645032{col 37}{space 1}   -2.06{col 46}{space 3}0.039{col 54}{space 4} -.662624{col 67}{space 3}-.0167425
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2} .2540046{col 26}{space 2} .1723237{col 37}{space 1}    1.47{col 46}{space 3}0.141{col 54}{space 4}-.0842889{col 67}{space 3} .5922981
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .0475622{col 26}{space 2} .3000282{col 37}{space 1}    0.16{col 46}{space 3}0.874{col 54}{space 4}-.5414315{col 67}{space 3} .6365558
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} -.167052{col 26}{space 2} .3018767{col 37}{space 1}   -0.55{col 46}{space 3}0.580{col 54}{space 4}-.7596746{col 67}{space 3} .4255705
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.6762558{col 26}{space 2} .3032689{col 37}{space 1}   -2.23{col 46}{space 3}0.026{col 54}{space 4}-1.271611{col 67}{space 3}-.0809002
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} 1.762884{col 26}{space 2} .3010698{col 37}{space 1}    5.86{col 46}{space 3}0.000{col 54}{space 4} 1.171845{col 67}{space 3} 2.353922
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .3951381{col 26}{space 2} .1653235{col 37}{space 1}    2.39{col 46}{space 3}0.017{col 54}{space 4} .0705869{col 67}{space 3} .7196893
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .2826935{col 26}{space 2} .2379798{col 37}{space 1}    1.19{col 46}{space 3}0.235{col 54}{space 4}-.1844913{col 67}{space 3} .7498783
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .3716494{col 26}{space 2} .2407016{col 37}{space 1}    1.54{col 46}{space 3}0.123{col 54}{space 4}-.1008786{col 67}{space 3} .8441773
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .3747314{col 26}{space 2}  .240634{col 37}{space 1}    1.56{col 46}{space 3}0.120{col 54}{space 4}-.0976639{col 67}{space 3} .8471266
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0582031{col 26}{space 2} .2119876{col 37}{space 1}   -0.27{col 46}{space 3}0.784{col 54}{space 4}-.4743619{col 67}{space 3} .3579556
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.1172463{col 26}{space 2} .2119649{col 37}{space 1}   -0.55{col 46}{space 3}0.580{col 54}{space 4}-.5333605{col 67}{space 3} .2988679
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2} -.221477{col 26}{space 2} .2110249{col 37}{space 1}   -1.05{col 46}{space 3}0.294{col 54}{space 4}-.6357457{col 67}{space 3} .1927918
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0378054{col 26}{space 2} .2112106{col 37}{space 1}    0.18{col 46}{space 3}0.858{col 54}{space 4} -.376828{col 67}{space 3} .4524387
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.1862501{col 26}{space 2} .2110038{col 37}{space 1}   -0.88{col 46}{space 3}0.378{col 54}{space 4}-.6004775{col 67}{space 3} .2279773
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .0842253{col 26}{space 2} .2421485{col 37}{space 1}    0.35{col 46}{space 3}0.728{col 54}{space 4}-.3911431{col 67}{space 3} .5595937
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.3289631{col 26}{space 2} .2206009{col 37}{space 1}   -1.49{col 46}{space 3}0.136{col 54}{space 4}-.7620308{col 67}{space 3} .1041046
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .2270428{col 26}{space 2} .2365169{col 37}{space 1}    0.96{col 46}{space 3}0.337{col 54}{space 4}-.2372701{col 67}{space 3} .6913557
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2}-.0559256{col 26}{space 2} .2406525{col 37}{space 1}   -0.23{col 46}{space 3}0.816{col 54}{space 4}-.5283573{col 67}{space 3} .4165061
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2}-.0176353{col 26}{space 2} .2413392{col 37}{space 1}   -0.07{col 46}{space 3}0.942{col 54}{space 4} -.491415{col 67}{space 3} .4561444
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.2007937{col 26}{space 2} .2143565{col 37}{space 1}   -0.94{col 46}{space 3}0.349{col 54}{space 4}-.6216029{col 67}{space 3} .2200156
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0915393{col 26}{space 2} .2130654{col 37}{space 1}   -0.43{col 46}{space 3}0.668{col 54}{space 4}-.5098141{col 67}{space 3} .3267354
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .2774077{col 26}{space 2} .2406525{col 37}{space 1}    1.15{col 46}{space 3}0.249{col 54}{space 4}-.1950239{col 67}{space 3} .7498394
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4633193{col 26}{space 2} .3063697{col 37}{space 1}    1.51{col 46}{space 3}0.131{col 54}{space 4}-.1381235{col 67}{space 3} 1.064762
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{stata `"shellout using `"Tables/will_act.tex"'"':Tables/will_act.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/will_act.txt""':seeout}
note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

      Source {c |}       SS       df       MS              Number of obs ={res}     777
{txt}{hline 13}{char +}{hline 30}           F( 26,   750) ={res}   16.76
    {txt}   Model {char |} {res}  436.22434    26  16.7778592           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 750.918517   750  1.00122469           {txt}R-squared     = {res} 0.3675
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.3455
    {txt}   Total {char |} {res} 1187.14286   776  1.52982327           {txt}Root MSE      = {res} 1.0006

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   goprotest{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}steal_upset {c |}{col 14}{res}{space 2} .3353566{col 26}{space 2} .0465833{col 37}{space 1}    7.20{col 46}{space 3}0.000{col 54}{space 4} .2439075{col 67}{space 3} .4268057
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.7092145{col 26}{space 2} .1745075{col 37}{space 1}   -4.06{col 46}{space 3}0.000{col 54}{space 4}-1.051796{col 67}{space 3}-.3666333
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.4457015{col 26}{space 2} .3296284{col 37}{space 1}   -1.35{col 46}{space 3}0.177{col 54}{space 4}-1.092806{col 67}{space 3} .2014027
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2}-.9628534{col 26}{space 2} .1736993{col 37}{space 1}   -5.54{col 46}{space 3}0.000{col 54}{space 4}-1.303848{col 67}{space 3}-.6218587
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2}-.0313053{col 26}{space 2} .1819639{col 37}{space 1}   -0.17{col 46}{space 3}0.863{col 54}{space 4}-.3885243{col 67}{space 3} .3259138
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.1579012{col 26}{space 2} .3196636{col 37}{space 1}   -0.49{col 46}{space 3}0.621{col 54}{space 4}-.7854431{col 67}{space 3} .4696407
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.6274912{col 26}{space 2} .3215168{col 37}{space 1}   -1.95{col 46}{space 3}0.051{col 54}{space 4}-1.258671{col 67}{space 3} .0036888
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.4150486{col 26}{space 2} .3230294{col 37}{space 1}   -1.28{col 46}{space 3}0.199{col 54}{space 4}-1.049198{col 67}{space 3} .2191009
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} 1.323893{col 26}{space 2}    .3208{col 37}{space 1}    4.13{col 46}{space 3}0.000{col 54}{space 4} .6941203{col 67}{space 3} 1.953666
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .1175198{col 26}{space 2} .1745604{col 37}{space 1}    0.67{col 46}{space 3}0.501{col 54}{space 4}-.2251654{col 67}{space 3}  .460205
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .1367598{col 26}{space 2} .2549213{col 37}{space 1}    0.54{col 46}{space 3}0.592{col 54}{space 4}-.3636843{col 67}{space 3}  .637204
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .2498643{col 26}{space 2} .2577476{col 37}{space 1}    0.97{col 46}{space 3}0.333{col 54}{space 4}-.2561282{col 67}{space 3} .7558568
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .1611103{col 26}{space 2} .2576691{col 37}{space 1}    0.63{col 46}{space 3}0.532{col 54}{space 4}-.3447281{col 67}{space 3} .6669487
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0178166{col 26}{space 2} .2238059{col 37}{space 1}   -0.08{col 46}{space 3}0.937{col 54}{space 4} -.457177{col 67}{space 3} .4215439
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} .1744613{col 26}{space 2} .2237819{col 37}{space 1}    0.78{col 46}{space 3}0.436{col 54}{space 4}-.2648521{col 67}{space 3} .6137747
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2} .1065505{col 26}{space 2} .2227895{col 37}{space 1}    0.48{col 46}{space 3}0.633{col 54}{space 4}-.3308146{col 67}{space 3} .5439156
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .4029482{col 26}{space 2} .2229856{col 37}{space 1}    1.81{col 46}{space 3}0.071{col 54}{space 4}-.0348019{col 67}{space 3} .8406984
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.0746529{col 26}{space 2} .2227672{col 37}{space 1}   -0.34{col 46}{space 3}0.738{col 54}{space 4}-.5119743{col 67}{space 3} .3626685
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.0521045{col 26}{space 2} .2592198{col 37}{space 1}   -0.20{col 46}{space 3}0.841{col 54}{space 4}-.5609872{col 67}{space 3} .4567783
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.0715285{col 26}{space 2} .2328993{col 37}{space 1}   -0.31{col 46}{space 3}0.759{col 54}{space 4}-.5287407{col 67}{space 3} .3856837
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .3487959{col 26}{space 2} .2533846{col 37}{space 1}    1.38{col 46}{space 3}0.169{col 54}{space 4}-.1486316{col 67}{space 3} .8462234
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .1092135{col 26}{space 2} .2576911{col 37}{space 1}    0.42{col 46}{space 3}0.672{col 54}{space 4}-.3966682{col 67}{space 3} .6150951
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .3559843{col 26}{space 2} .2584016{col 37}{space 1}    1.38{col 46}{space 3}0.169{col 54}{space 4}-.1512921{col 67}{space 3} .8632607
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} .2420442{col 26}{space 2} .2263069{col 37}{space 1}    1.07{col 46}{space 3}0.285{col 54}{space 4}-.2022261{col 67}{space 3} .6863145
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2} .0181793{col 26}{space 2} .2249438{col 37}{space 1}    0.08{col 46}{space 3}0.936{col 54}{space 4}-.4234151{col 67}{space 3} .4597737
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .3536579{col 26}{space 2} .2576911{col 37}{space 1}    1.37{col 46}{space 3}0.170{col 54}{space 4}-.1522237{col 67}{space 3} .8595395
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7365636{col 26}{space 2} .3258871{col 37}{space 1}    2.26{col 46}{space 3}0.024{col 54}{space 4} .0968041{col 67}{space 3} 1.376323
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{stata `"shellout using `"Tables/will_act.tex"'"':Tables/will_act.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/will_act.txt""':seeout}
note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

      Source {c |}       SS       df       MS              Number of obs ={res}     778
{txt}{hline 13}{char +}{hline 30}           F( 26,   751) ={res}   14.61
    {txt}   Model {char |} {res}  390.06732    26  15.0025892           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res}  771.22831   751  1.02693517           {txt}R-squared     = {res} 0.3359
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.3129
    {txt}   Total {char |} {res} 1161.29563   777  1.49458897           {txt}Root MSE      = {res} 1.0134

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}campaign_a~t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}steal_upset {c |}{col 14}{res}{space 2} .3601383{col 26}{space 2} .0471717{col 37}{space 1}    7.63{col 46}{space 3}0.000{col 54}{space 4} .2675342{col 67}{space 3} .4527424
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.2223956{col 26}{space 2} .1765238{col 37}{space 1}   -1.26{col 46}{space 3}0.208{col 54}{space 4}-.5689344{col 67}{space 3} .1241432
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.5465077{col 26}{space 2} .3310069{col 37}{space 1}   -1.65{col 46}{space 3}0.099{col 54}{space 4}-1.196317{col 67}{space 3} .1033011
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2}-.8928109{col 26}{space 2} .1758899{col 37}{space 1}   -5.08{col 46}{space 3}0.000{col 54}{space 4}-1.238105{col 67}{space 3}-.5475165
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2} .2544937{col 26}{space 2} .1842518{col 37}{space 1}    1.38{col 46}{space 3}0.168{col 54}{space 4}-.1072162{col 67}{space 3} .6162036
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2} .1457808{col 26}{space 2} .3207959{col 37}{space 1}    0.45{col 46}{space 3}0.650{col 54}{space 4}-.4839825{col 67}{space 3} .7755441
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} -.429737{col 26}{space 2} .3227723{col 37}{space 1}   -1.33{col 46}{space 3}0.183{col 54}{space 4} -1.06338{col 67}{space 3} .2039064
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2} .1168158{col 26}{space 2} .3242609{col 37}{space 1}    0.36{col 46}{space 3}0.719{col 54}{space 4}-.5197498{col 67}{space 3} .7533813
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} 1.180174{col 26}{space 2} .3219095{col 37}{space 1}    3.67{col 46}{space 3}0.000{col 54}{space 4} .5482242{col 67}{space 3} 1.812123
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2} .1067911{col 26}{space 2} .1767671{col 37}{space 1}    0.60{col 46}{space 3}0.546{col 54}{space 4}-.2402252{col 67}{space 3} .4538075
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .2810123{col 26}{space 2} .2544526{col 37}{space 1}    1.10{col 46}{space 3}0.270{col 54}{space 4}-.2185106{col 67}{space 3} .7805353
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2}  .569011{col 26}{space 2} .2573627{col 37}{space 1}    2.21{col 46}{space 3}0.027{col 54}{space 4} .0637751{col 67}{space 3} 1.074247
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .2819091{col 26}{space 2} .2572905{col 37}{space 1}    1.10{col 46}{space 3}0.274{col 54}{space 4}-.2231849{col 67}{space 3} .7870032
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.3215982{col 26}{space 2} .2266612{col 37}{space 1}   -1.42{col 46}{space 3}0.156{col 54}{space 4}-.7665631{col 67}{space 3} .1233667
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2}-.0665086{col 26}{space 2} .2266369{col 37}{space 1}   -0.29{col 46}{space 3}0.769{col 54}{space 4}-.5114259{col 67}{space 3} .3784086
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.4189938{col 26}{space 2} .2256318{col 37}{space 1}   -1.86{col 46}{space 3}0.064{col 54}{space 4}-.8619379{col 67}{space 3} .0239503
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .0644364{col 26}{space 2} .2258304{col 37}{space 1}    0.29{col 46}{space 3}0.775{col 54}{space 4}-.3788976{col 67}{space 3} .5077703
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.3833446{col 26}{space 2} .2256093{col 37}{space 1}   -1.70{col 46}{space 3}0.090{col 54}{space 4}-.8262445{col 67}{space 3} .0595552
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2} .3187017{col 26}{space 2} .2589098{col 37}{space 1}    1.23{col 46}{space 3}0.219{col 54}{space 4}-.1895713{col 67}{space 3} .8269747
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.4908919{col 26}{space 2} .2358707{col 37}{space 1}   -2.08{col 46}{space 3}0.038{col 54}{space 4}-.9539362{col 67}{space 3}-.0278476
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .4363443{col 26}{space 2} .2528884{col 37}{space 1}    1.73{col 46}{space 3}0.085{col 54}{space 4}-.0601079{col 67}{space 3} .9327966
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .3183505{col 26}{space 2} .2573103{col 37}{space 1}    1.24{col 46}{space 3}0.216{col 54}{space 4}-.1867825{col 67}{space 3} .8234835
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .5171475{col 26}{space 2} .2580445{col 37}{space 1}    2.00{col 46}{space 3}0.045{col 54}{space 4} .0105732{col 67}{space 3} 1.023722
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2}-.3054195{col 26}{space 2} .2291941{col 37}{space 1}   -1.33{col 46}{space 3}0.183{col 54}{space 4}-.7553568{col 67}{space 3} .1445178
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.3630298{col 26}{space 2} .2278137{col 37}{space 1}   -1.59{col 46}{space 3}0.111{col 54}{space 4}-.8102571{col 67}{space 3} .0841975
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .2516838{col 26}{space 2} .2573103{col 37}{space 1}    0.98{col 46}{space 3}0.328{col 54}{space 4}-.2534491{col 67}{space 3} .7568168
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.267887{col 26}{space 2} .3275763{col 37}{space 1}    3.87{col 46}{space 3}0.000{col 54}{space 4} .6248128{col 67}{space 3} 1.910961
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{stata `"shellout using `"Tables/will_act.tex"'"':Tables/will_act.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/will_act.txt""':seeout}

{com}. 
.                 
.                 
. // TABLE 9: OLS regression linking perceived corruption severity in the conjoint experiment; the degree to which citizens report being upset about a hypothetical corruption scandal; and self-report political action. 
.         reg steal_upset avg_rank $fe $townfe
{txt}note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

      Source {c |}       SS       df       MS              Number of obs ={res}     778
{txt}{hline 13}{char +}{hline 30}           F( 26,   751) ={res}    7.26
    {txt}   Model {char |} {res} 115.350651    26  4.43656349           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 459.091509   751  .611306936           {txt}R-squared     = {res} 0.2008
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.1731
    {txt}   Total {char |} {res} 574.442159   777  .739307798           {txt}Root MSE      = {res} .78186

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} steal_upset{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}avg_rank {c |}{col 14}{res}{space 2}  .180274{col 26}{space 2} .0906671{col 37}{space 1}    1.99{col 46}{space 3}0.047{col 54}{space 4} .0022828{col 67}{space 3} .3582652
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2} .2705151{col 26}{space 2}   .13785{col 37}{space 1}    1.96{col 46}{space 3}0.050{col 54}{space 4} -.000102{col 67}{space 3} .5411323
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2} -.208851{col 26}{space 2} .2554927{col 37}{space 1}   -0.82{col 46}{space 3}0.414{col 54}{space 4}-.7104158{col 67}{space 3} .2927137
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2} .0834751{col 26}{space 2} .1379049{col 37}{space 1}    0.61{col 46}{space 3}0.545{col 54}{space 4}-.1872497{col 67}{space 3}    .3542
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2}-.2534586{col 26}{space 2} .1430384{col 37}{space 1}   -1.77{col 46}{space 3}0.077{col 54}{space 4}-.5342613{col 67}{space 3} .0273442
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.0393266{col 26}{space 2} .2533584{col 37}{space 1}   -0.16{col 46}{space 3}0.877{col 54}{space 4}-.5367014{col 67}{space 3} .4580483
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2}-.7410318{col 26}{space 2}  .247662{col 37}{space 1}   -2.99{col 46}{space 3}0.003{col 54}{space 4}-1.227224{col 67}{space 3}-.2548397
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.1315165{col 26}{space 2} .2515433{col 37}{space 1}   -0.52{col 46}{space 3}0.601{col 54}{space 4}-.6253281{col 67}{space 3} .3622951
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} .4356702{col 26}{space 2}  .253144{col 37}{space 1}    1.72{col 46}{space 3}0.086{col 54}{space 4}-.0612837{col 67}{space 3} .9326242
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.3596732{col 26}{space 2} .1359035{col 37}{space 1}   -2.65{col 46}{space 3}0.008{col 54}{space 4}-.6264692{col 67}{space 3}-.0928773
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .1452498{col 26}{space 2} .1964752{col 37}{space 1}    0.74{col 46}{space 3}0.460{col 54}{space 4}-.2404562{col 67}{space 3} .5309557
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2} .1572253{col 26}{space 2} .1984828{col 37}{space 1}    0.79{col 46}{space 3}0.429{col 54}{space 4}-.2324218{col 67}{space 3} .5468725
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .1035785{col 26}{space 2} .1985671{col 37}{space 1}    0.52{col 46}{space 3}0.602{col 54}{space 4}-.2862341{col 67}{space 3} .4933911
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0637358{col 26}{space 2} .1754922{col 37}{space 1}   -0.36{col 46}{space 3}0.717{col 54}{space 4}-.4082494{col 67}{space 3} .2807777
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} .1008334{col 26}{space 2} .1759392{col 37}{space 1}    0.57{col 46}{space 3}0.567{col 54}{space 4}-.2445577{col 67}{space 3} .4462245
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.0870328{col 26}{space 2} .1746413{col 37}{space 1}   -0.50{col 46}{space 3}0.618{col 54}{space 4}-.4298759{col 67}{space 3} .2558104
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .2568743{col 26}{space 2} .1744879{col 37}{space 1}    1.47{col 46}{space 3}0.141{col 54}{space 4}-.0856678{col 67}{space 3} .5994164
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.0750911{col 26}{space 2} .1742994{col 37}{space 1}   -0.43{col 46}{space 3}0.667{col 54}{space 4}-.4172632{col 67}{space 3} .2670809
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}-.1133911{col 26}{space 2} .1997386{col 37}{space 1}   -0.57{col 46}{space 3}0.570{col 54}{space 4}-.5055035{col 67}{space 3} .2787212
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2} .2067903{col 26}{space 2} .1822248{col 37}{space 1}    1.13{col 46}{space 3}0.257{col 54}{space 4}-.1509403{col 67}{space 3} .5645209
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2} .0964871{col 26}{space 2} .1952351{col 37}{space 1}    0.49{col 46}{space 3}0.621{col 54}{space 4}-.2867844{col 67}{space 3} .4797586
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2} .0932512{col 26}{space 2} .1987612{col 37}{space 1}    0.47{col 46}{space 3}0.639{col 54}{space 4}-.2969425{col 67}{space 3}  .483445
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .0792498{col 26}{space 2} .1990706{col 37}{space 1}    0.40{col 46}{space 3}0.691{col 54}{space 4}-.3115512{col 67}{space 3} .4700507
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} .1959064{col 26}{space 2} .1767799{col 37}{space 1}    1.11{col 46}{space 3}0.268{col 54}{space 4}-.1511351{col 67}{space 3} .5429478
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.0869112{col 26}{space 2} .1757712{col 37}{space 1}   -0.49{col 46}{space 3}0.621{col 54}{space 4}-.4319726{col 67}{space 3} .2581502
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .1152847{col 26}{space 2} .1984823{col 37}{space 1}    0.58{col 46}{space 3}0.562{col 54}{space 4}-.2743613{col 67}{space 3} .5049307
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  3.62315{col 26}{space 2} .4159068{col 37}{space 1}    8.71{col 46}{space 3}0.000{col 54}{space 4} 2.806672{col 67}{space 3} 4.439628
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/avgrank", replace tex(frag) bdec(3) drop($fe $townfe) ctitle(Steal Upset)
{txt}{stata `"shellout using `"Tables/avgrank.tex"'"':Tables/avgrank.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/avgrank.txt""':seeout}

{com}.         reg avg_action avg_rank $fe $townfe
{txt}note: e_4 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

      Source {c |}       SS       df       MS              Number of obs ={res}     778
{txt}{hline 13}{char +}{hline 30}           F( 26,   751) ={res}   21.32
    {txt}   Model {char |} {res} 267.086609    26  10.2725619           {txt}Prob > F      = {res} 0.0000
    {txt}Residual {char |} {res} 361.792006   751  .481747012           {txt}R-squared     = {res} 0.4247
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.4048
    {txt}   Total {char |} {res} 628.878615   777  .809367587           {txt}Root MSE      = {res} .69408

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  avg_action{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}avg_rank {c |}{col 14}{res}{space 2} .2297402{col 26}{space 2} .0804878{col 37}{space 1}    2.85{col 46}{space 3}0.004{col 54}{space 4} .0717324{col 67}{space 3} .3877479
{txt}{space 9}e_1 {c |}{col 14}{res}{space 2}-.3499061{col 26}{space 2} .1223733{col 37}{space 1}   -2.86{col 46}{space 3}0.004{col 54}{space 4}-.5901405{col 67}{space 3}-.1096717
{txt}{space 9}e_2 {c |}{col 14}{res}{space 2}-.3679178{col 26}{space 2}  .226808{col 37}{space 1}   -1.62{col 46}{space 3}0.105{col 54}{space 4}-.8131708{col 67}{space 3} .0773352
{txt}{space 9}e_3 {c |}{col 14}{res}{space 2}-.4525507{col 26}{space 2}  .122422{col 37}{space 1}   -3.70{col 46}{space 3}0.000{col 54}{space 4}-.6928807{col 67}{space 3}-.2122207
{txt}{space 9}e_4 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 9}e_5 {c |}{col 14}{res}{space 2}-.1315523{col 26}{space 2} .1269792{col 37}{space 1}   -1.04{col 46}{space 3}0.301{col 54}{space 4}-.3808287{col 67}{space 3} .1177241
{txt}{space 9}e_6 {c |}{col 14}{res}{space 2}-.1651281{col 26}{space 2} .2249133{col 37}{space 1}   -0.73{col 46}{space 3}0.463{col 54}{space 4}-.6066617{col 67}{space 3} .2764054
{txt}{space 9}e_7 {c |}{col 14}{res}{space 2} -.498959{col 26}{space 2} .2198564{col 37}{space 1}   -2.27{col 46}{space 3}0.024{col 54}{space 4}-.9305652{col 67}{space 3}-.0673527
{txt}{space 9}e_8 {c |}{col 14}{res}{space 2}-.4256733{col 26}{space 2}  .223302{col 37}{space 1}   -1.91{col 46}{space 3}0.057{col 54}{space 4}-.8640436{col 67}{space 3} .0126971
{txt}{space 9}e_9 {c |}{col 14}{res}{space 2} 1.315715{col 26}{space 2}  .224723{col 37}{space 1}    5.85{col 46}{space 3}0.000{col 54}{space 4} .8745555{col 67}{space 3} 1.756875
{txt}{space 8}e_10 {c |}{col 14}{res}{space 2}-.0073169{col 26}{space 2} .1206453{col 37}{space 1}   -0.06{col 46}{space 3}0.952{col 54}{space 4}-.2441591{col 67}{space 3} .2295253
{txt}{space 4}townfe_1 {c |}{col 14}{res}{space 2} .3300886{col 26}{space 2} .1744165{col 37}{space 1}    1.89{col 46}{space 3}0.059{col 54}{space 4}-.0123133{col 67}{space 3} .6724906
{txt}{space 4}townfe_2 {c |}{col 14}{res}{space 2}  .453605{col 26}{space 2} .1761987{col 37}{space 1}    2.57{col 46}{space 3}0.010{col 54}{space 4} .1077044{col 67}{space 3} .7995056
{txt}{space 4}townfe_3 {c |}{col 14}{res}{space 2} .2090862{col 26}{space 2} .1762735{col 37}{space 1}    1.19{col 46}{space 3}0.236{col 54}{space 4}-.1369613{col 67}{space 3} .5551337
{txt}{space 4}townfe_4 {c |}{col 14}{res}{space 2}-.0620814{col 26}{space 2} .1557893{col 37}{space 1}   -0.40{col 46}{space 3}0.690{col 54}{space 4}-.3679157{col 67}{space 3} .2437529
{txt}{space 4}townfe_5 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}townfe_6 {c |}{col 14}{res}{space 2} .1160723{col 26}{space 2} .1561861{col 37}{space 1}    0.74{col 46}{space 3}0.458{col 54}{space 4} -.190541{col 67}{space 3} .4226856
{txt}{space 4}townfe_7 {c |}{col 14}{res}{space 2}-.1944376{col 26}{space 2} .1550339{col 37}{space 1}   -1.25{col 46}{space 3}0.210{col 54}{space 4}-.4987891{col 67}{space 3} .1099138
{txt}{space 4}townfe_8 {c |}{col 14}{res}{space 2} .2407854{col 26}{space 2} .1548978{col 37}{space 1}    1.55{col 46}{space 3}0.120{col 54}{space 4}-.0632988{col 67}{space 3} .5448696
{txt}{space 4}townfe_9 {c |}{col 14}{res}{space 2}-.1851844{col 26}{space 2} .1547305{col 37}{space 1}   -1.20{col 46}{space 3}0.232{col 54}{space 4}-.4889401{col 67}{space 3} .1185713
{txt}{space 3}townfe_10 {c |}{col 14}{res}{space 2}   .20136{col 26}{space 2} .1773135{col 37}{space 1}    1.14{col 46}{space 3}0.256{col 54}{space 4}-.1467291{col 67}{space 3} .5494491
{txt}{space 3}townfe_11 {c |}{col 14}{res}{space 2}-.1814814{col 26}{space 2} .1617661{col 37}{space 1}   -1.12{col 46}{space 3}0.262{col 54}{space 4}-.4990488{col 67}{space 3} .1360861
{txt}{space 3}townfe_12 {c |}{col 14}{res}{space 2}   .42513{col 26}{space 2} .1733157{col 37}{space 1}    2.45{col 46}{space 3}0.014{col 54}{space 4} .0848892{col 67}{space 3} .7653708
{txt}{space 3}townfe_13 {c |}{col 14}{res}{space 2}  .284272{col 26}{space 2} .1764459{col 37}{space 1}    1.61{col 46}{space 3}0.108{col 54}{space 4}-.0621138{col 67}{space 3} .6306579
{txt}{space 3}townfe_14 {c |}{col 14}{res}{space 2} .3583356{col 26}{space 2} .1767205{col 37}{space 1}    2.03{col 46}{space 3}0.043{col 54}{space 4} .0114107{col 67}{space 3} .7052605
{txt}{space 3}townfe_15 {c |}{col 14}{res}{space 2} .0096821{col 26}{space 2} .1569324{col 37}{space 1}    0.06{col 46}{space 3}0.951{col 54}{space 4}-.2983962{col 67}{space 3} .3177605
{txt}{space 3}townfe_16 {c |}{col 14}{res}{space 2}-.1051756{col 26}{space 2}  .156037{col 37}{space 1}   -0.67{col 46}{space 3}0.500{col 54}{space 4}-.4114962{col 67}{space 3}  .201145
{txt}{space 3}townfe_17 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}townfe_18 {c |}{col 14}{res}{space 2} .4234625{col 26}{space 2} .1761982{col 37}{space 1}    2.40{col 46}{space 3}0.016{col 54}{space 4} .0775628{col 67}{space 3} .7693621
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.599427{col 26}{space 2} .3692121{col 37}{space 1}    4.33{col 46}{space 3}0.000{col 54}{space 4} .8746161{col 67}{space 3} 2.324237
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/avgrank", append tex(frag) bdec(3) drop($fe $townfe) ctitle(Likelihood of Action (Avg))
{txt}{stata `"shellout using `"Tables/avgrank.tex"'"':Tables/avgrank.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/avgrank.txt""':seeout}

{com}.         
.         
. 
. ********        OPEN DATASET AND SET GLOBALS FOR APPENDIX C5-C6
.         
.         * Open profile-level dataset
.         use "profile_level_clean.dta", clear
{txt}
{com}. 
.         * Set globals for analysis: enumerator fixed effects and town fixed effects
.                 gl fe "e_* "
{txt}
{com}.                 gl townfe "townfe_*"
{txt}
{com}.         
. ********        APPENDIX C5: INTERACTION MODEL  
.         
.         * Define global of all interactions
.         global interacts "elect_* local_* tax_* transfer_* kinvill_* buyel_*"
{txt}
{com}. 
. //  TABLE 10: Interaction effects
.         reg chosen elect local tax transfer kinvill buyel water health educ infra $interacts $fe $townfe, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    6224
                                                       {txt}F( 72,   777) ={res}   12.32
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1031
                                                       {txt}Root MSE      = {res} .47634

{txt}{ralign 82:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}          chosen{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}elect {c |}{col 18}{res}{space 2} .1110054{col 30}{space 2} .0378745{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0366569{col 71}{space 3} .1853538
{txt}{space 11}local {c |}{col 18}{res}{space 2}-.0147853{col 30}{space 2} .0372664{col 41}{space 1}   -0.40{col 50}{space 3}0.692{col 58}{space 4}-.0879401{col 71}{space 3} .0583695
{txt}{space 13}tax {c |}{col 18}{res}{space 2} .1521593{col 30}{space 2} .0432216{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4} .0673143{col 71}{space 3} .2370043
{txt}{space 8}transfer {c |}{col 18}{res}{space 2} .0052279{col 30}{space 2} .0438279{col 41}{space 1}    0.12{col 50}{space 3}0.905{col 58}{space 4}-.0808072{col 71}{space 3} .0912631
{txt}{space 9}kinvill {c |}{col 18}{res}{space 2}-.1761295{col 30}{space 2} .0418826{col 41}{space 1}   -4.21{col 50}{space 3}0.000{col 58}{space 4}-.2583459{col 71}{space 3} -.093913
{txt}{space 11}buyel {c |}{col 18}{res}{space 2}-.1030989{col 30}{space 2} .0441847{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-.1898344{col 71}{space 3}-.0163634
{txt}{space 11}water {c |}{col 18}{res}{space 2} .1735326{col 30}{space 2} .0509663{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0734846{col 71}{space 3} .2735806
{txt}{space 10}health {c |}{col 18}{res}{space 2} .3007483{col 30}{space 2} .0486377{col 41}{space 1}    6.18{col 50}{space 3}0.000{col 58}{space 4} .2052715{col 71}{space 3} .3962251
{txt}{space 12}educ {c |}{col 18}{res}{space 2} .2006859{col 30}{space 2} .0516988{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4}    .0992{col 71}{space 3} .3021719
{txt}{space 11}infra {c |}{col 18}{res}{space 2} .1616144{col 30}{space 2} .0491486{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0651346{col 71}{space 3} .2580941
{txt}{space 5}elect_local {c |}{col 18}{res}{space 2}-.0070405{col 30}{space 2} .0248819{col 41}{space 1}   -0.28{col 50}{space 3}0.777{col 58}{space 4}-.0558842{col 71}{space 3} .0418032
{txt}{space 7}elect_tax {c |}{col 18}{res}{space 2} -.009774{col 30}{space 2} .0293082{col 41}{space 1}   -0.33{col 50}{space 3}0.739{col 58}{space 4}-.0673067{col 71}{space 3} .0477587
{txt}{space 2}elect_transfer {c |}{col 18}{res}{space 2} .0327868{col 30}{space 2} .0306758{col 41}{space 1}    1.07{col 50}{space 3}0.285{col 58}{space 4}-.0274305{col 71}{space 3} .0930041
{txt}{space 3}elect_kinvill {c |}{col 18}{res}{space 2} .0158497{col 30}{space 2} .0293903{col 41}{space 1}    0.54{col 50}{space 3}0.590{col 58}{space 4} -.041844{col 71}{space 3} .0735435
{txt}{space 5}elect_buyel {c |}{col 18}{res}{space 2}-.0356453{col 30}{space 2} .0296128{col 41}{space 1}   -1.20{col 50}{space 3}0.229{col 58}{space 4}-.0937759{col 71}{space 3} .0224853
{txt}{space 5}elect_water {c |}{col 18}{res}{space 2}-.0366025{col 30}{space 2} .0382872{col 41}{space 1}   -0.96{col 50}{space 3}0.339{col 58}{space 4}-.1117611{col 71}{space 3}  .038556
{txt}{space 4}elect_health {c |}{col 18}{res}{space 2}-.0226269{col 30}{space 2} .0380432{col 41}{space 1}   -0.59{col 50}{space 3}0.552{col 58}{space 4}-.0973064{col 71}{space 3} .0520527
{txt}{space 6}elect_educ {c |}{col 18}{res}{space 2} .0418876{col 30}{space 2} .0396655{col 41}{space 1}    1.06{col 50}{space 3}0.291{col 58}{space 4}-.0359767{col 71}{space 3} .1197519
{txt}{space 5}elect_infra {c |}{col 18}{res}{space 2}-.0393656{col 30}{space 2} .0384947{col 41}{space 1}   -1.02{col 50}{space 3}0.307{col 58}{space 4}-.1149316{col 71}{space 3} .0362003
{txt}{space 7}local_tax {c |}{col 18}{res}{space 2} .0564753{col 30}{space 2} .0296708{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0017692{col 71}{space 3} .1147198
{txt}{space 2}local_transfer {c |}{col 18}{res}{space 2} .0187744{col 30}{space 2} .0293074{col 41}{space 1}    0.64{col 50}{space 3}0.522{col 58}{space 4}-.0387568{col 71}{space 3} .0763055
{txt}{space 3}local_kinvill {c |}{col 18}{res}{space 2} .0197359{col 30}{space 2} .0288211{col 41}{space 1}    0.68{col 50}{space 3}0.494{col 58}{space 4}-.0368406{col 71}{space 3} .0763123
{txt}{space 5}local_buyel {c |}{col 18}{res}{space 2} .0260492{col 30}{space 2} .0296097{col 41}{space 1}    0.88{col 50}{space 3}0.379{col 58}{space 4}-.0320753{col 71}{space 3} .0841738
{txt}{space 5}local_water {c |}{col 18}{res}{space 2}-.0131916{col 30}{space 2} .0383746{col 41}{space 1}   -0.34{col 50}{space 3}0.731{col 58}{space 4}-.0885217{col 71}{space 3} .0621385
{txt}{space 4}local_health {c |}{col 18}{res}{space 2}-.1054326{col 30}{space 2} .0373389{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.1787297{col 71}{space 3}-.0321356
{txt}{space 6}local_educ {c |}{col 18}{res}{space 2}-.0425658{col 30}{space 2} .0372757{col 41}{space 1}   -1.14{col 50}{space 3}0.254{col 58}{space 4}-.1157388{col 71}{space 3} .0306072
{txt}{space 5}local_infra {c |}{col 18}{res}{space 2} -.025785{col 30}{space 2}  .038046{col 41}{space 1}   -0.68{col 50}{space 3}0.498{col 58}{space 4}-.1004701{col 71}{space 3} .0489002
{txt}{space 5}tax_kinvill {c |}{col 18}{res}{space 2} .0155201{col 30}{space 2} .0357278{col 41}{space 1}    0.43{col 50}{space 3}0.664{col 58}{space 4}-.0546143{col 71}{space 3} .0856545
{txt}{space 7}tax_buyel {c |}{col 18}{res}{space 2} .0388379{col 30}{space 2} .0355105{col 41}{space 1}    1.09{col 50}{space 3}0.274{col 58}{space 4}-.0308701{col 71}{space 3} .1085459
{txt}{space 7}tax_water {c |}{col 18}{res}{space 2} .0738663{col 30}{space 2}  .046709{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4}-.0178246{col 71}{space 3} .1655571
{txt}{space 6}tax_health {c |}{col 18}{res}{space 2} .0138057{col 30}{space 2} .0455448{col 41}{space 1}    0.30{col 50}{space 3}0.762{col 58}{space 4}-.0755998{col 71}{space 3} .1032111
{txt}{space 8}tax_educ {c |}{col 18}{res}{space 2} -.020905{col 30}{space 2} .0449612{col 41}{space 1}   -0.46{col 50}{space 3}0.642{col 58}{space 4}-.1091648{col 71}{space 3} .0673548
{txt}{space 7}tax_infra {c |}{col 18}{res}{space 2}  .013714{col 30}{space 2} .0464591{col 41}{space 1}    0.30{col 50}{space 3}0.768{col 58}{space 4}-.0774862{col 71}{space 3} .1049141
{txt}transfer_kinvill {c |}{col 18}{res}{space 2} .0196661{col 30}{space 2} .0372917{col 41}{space 1}    0.53{col 50}{space 3}0.598{col 58}{space 4}-.0535383{col 71}{space 3} .0928705
{txt}{space 2}transfer_buyel {c |}{col 18}{res}{space 2} .0006326{col 30}{space 2} .0379054{col 41}{space 1}    0.02{col 50}{space 3}0.987{col 58}{space 4}-.0737765{col 71}{space 3} .0750417
{txt}{space 2}transfer_water {c |}{col 18}{res}{space 2}-.0197205{col 30}{space 2} .0484702{col 41}{space 1}   -0.41{col 50}{space 3}0.684{col 58}{space 4}-.1148687{col 71}{space 3} .0754276
{txt}{space 1}transfer_health {c |}{col 18}{res}{space 2} .0259498{col 30}{space 2} .0459591{col 41}{space 1}    0.56{col 50}{space 3}0.572{col 58}{space 4}-.0642689{col 71}{space 3} .1161685
{txt}{space 3}transfer_educ {c |}{col 18}{res}{space 2}-.0018509{col 30}{space 2}   .04437{col 41}{space 1}   -0.04{col 50}{space 3}0.967{col 58}{space 4}-.0889502{col 71}{space 3} .0852485
{txt}{space 2}transfer_infra {c |}{col 18}{res}{space 2}-.0478297{col 30}{space 2} .0467243{col 41}{space 1}   -1.02{col 50}{space 3}0.306{col 58}{space 4}-.1395505{col 71}{space 3} .0438911
{txt}{space 3}kinvill_water {c |}{col 18}{res}{space 2}-.1079866{col 30}{space 2} .0449936{col 41}{space 1}   -2.40{col 50}{space 3}0.017{col 58}{space 4}  -.19631{col 71}{space 3}-.0196633
{txt}{space 2}kinvill_health {c |}{col 18}{res}{space 2} -.021431{col 30}{space 2} .0459714{col 41}{space 1}   -0.47{col 50}{space 3}0.641{col 58}{space 4}-.1116738{col 71}{space 3} .0688119
{txt}{space 4}kinvill_educ {c |}{col 18}{res}{space 2}-.0931684{col 30}{space 2} .0463619{col 41}{space 1}   -2.01{col 50}{space 3}0.045{col 58}{space 4}-.1841778{col 71}{space 3} -.002159
{txt}{space 3}kinvill_infra {c |}{col 18}{res}{space 2}-.0353986{col 30}{space 2} .0466134{col 41}{space 1}   -0.76{col 50}{space 3}0.448{col 58}{space 4}-.1269016{col 71}{space 3} .0561044
{txt}{space 5}buyel_water {c |}{col 18}{res}{space 2}-.1437813{col 30}{space 2} .0481385{col 41}{space 1}   -2.99{col 50}{space 3}0.003{col 58}{space 4}-.2382783{col 71}{space 3}-.0492844
{txt}{space 4}buyel_health {c |}{col 18}{res}{space 2} .0074764{col 30}{space 2} .0452828{col 41}{space 1}    0.17{col 50}{space 3}0.869{col 58}{space 4}-.0814147{col 71}{space 3} .0963676
{txt}{space 6}buyel_educ {c |}{col 18}{res}{space 2}-.0797601{col 30}{space 2} .0468341{col 41}{space 1}   -1.70{col 50}{space 3}0.089{col 58}{space 4}-.1716965{col 71}{space 3} .0121762
{txt}{space 5}buyel_infra {c |}{col 18}{res}{space 2}-.0464014{col 30}{space 2}  .046362{col 41}{space 1}   -1.00{col 50}{space 3}0.317{col 58}{space 4}-.1374109{col 71}{space 3} .0446081
{txt}{space 13}e_1 {c |}{col 18}{res}{space 2}-.0165238{col 30}{space 2} .0184273{col 41}{space 1}   -0.90{col 50}{space 3}0.370{col 58}{space 4}-.0526969{col 71}{space 3} .0196494
{txt}{space 13}e_2 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 13}e_3 {c |}{col 18}{res}{space 2}-.0265018{col 30}{space 2} .0184367{col 41}{space 1}   -1.44{col 50}{space 3}0.151{col 58}{space 4}-.0626934{col 71}{space 3} .0096899
{txt}{space 13}e_4 {c |}{col 18}{res}{space 2}-.0050527{col 30}{space 2} .0193927{col 41}{space 1}   -0.26{col 50}{space 3}0.795{col 58}{space 4} -.043121{col 71}{space 3} .0330156
{txt}{space 13}e_5 {c |}{col 18}{res}{space 2}-.0043167{col 30}{space 2} .0183105{col 41}{space 1}   -0.24{col 50}{space 3}0.814{col 58}{space 4}-.0402605{col 71}{space 3} .0316271
{txt}{space 13}e_6 {c |}{col 18}{res}{space 2}-.0086233{col 30}{space 2} .0097313{col 41}{space 1}   -0.89{col 50}{space 3}0.376{col 58}{space 4} -.027726{col 71}{space 3} .0104795
{txt}{space 13}e_7 {c |}{col 18}{res}{space 2}-.0071406{col 30}{space 2} .0098019{col 41}{space 1}   -0.73{col 50}{space 3}0.467{col 58}{space 4}-.0263819{col 71}{space 3} .0121008
{txt}{space 13}e_8 {c |}{col 18}{res}{space 2}-.0033445{col 30}{space 2} .0103326{col 41}{space 1}   -0.32{col 50}{space 3}0.746{col 58}{space 4}-.0236277{col 71}{space 3} .0169386
{txt}{space 13}e_9 {c |}{col 18}{res}{space 2} .0017251{col 30}{space 2} .0100772{col 41}{space 1}    0.17{col 50}{space 3}0.864{col 58}{space 4}-.0180566{col 71}{space 3} .0215069
{txt}{space 12}e_10 {c |}{col 18}{res}{space 2}-.0089816{col 30}{space 2} .0183833{col 41}{space 1}   -0.49{col 50}{space 3}0.625{col 58}{space 4}-.0450684{col 71}{space 3} .0271052
{txt}{space 8}townfe_1 {c |}{col 18}{res}{space 2}-.0043601{col 30}{space 2} .0151519{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.0341036{col 71}{space 3} .0253833
{txt}{space 8}townfe_2 {c |}{col 18}{res}{space 2} .0219489{col 30}{space 2} .0157492{col 41}{space 1}    1.39{col 50}{space 3}0.164{col 58}{space 4}-.0089671{col 71}{space 3} .0528649
{txt}{space 8}townfe_3 {c |}{col 18}{res}{space 2}-.0006748{col 30}{space 2} .0145911{col 41}{space 1}   -0.05{col 50}{space 3}0.963{col 58}{space 4}-.0293175{col 71}{space 3} .0279679
{txt}{space 8}townfe_4 {c |}{col 18}{res}{space 2} .0091757{col 30}{space 2} .0125017{col 41}{space 1}    0.73{col 50}{space 3}0.463{col 58}{space 4}-.0153654{col 71}{space 3} .0337167
{txt}{space 8}townfe_5 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 8}townfe_6 {c |}{col 18}{res}{space 2}-.0068013{col 30}{space 2} .0125489{col 41}{space 1}   -0.54{col 50}{space 3}0.588{col 58}{space 4} -.031435{col 71}{space 3} .0178325
{txt}{space 8}townfe_7 {c |}{col 18}{res}{space 2} .0004785{col 30}{space 2} .0123336{col 41}{space 1}    0.04{col 50}{space 3}0.969{col 58}{space 4}-.0237327{col 71}{space 3} .0246896
{txt}{space 8}townfe_8 {c |}{col 18}{res}{space 2} .0121104{col 30}{space 2} .0122297{col 41}{space 1}    0.99{col 50}{space 3}0.322{col 58}{space 4}-.0118968{col 71}{space 3} .0361176
{txt}{space 8}townfe_9 {c |}{col 18}{res}{space 2} .0037329{col 30}{space 2} .0130387{col 41}{space 1}    0.29{col 50}{space 3}0.775{col 58}{space 4}-.0218623{col 71}{space 3} .0293282
{txt}{space 7}townfe_10 {c |}{col 18}{res}{space 2} .0056737{col 30}{space 2} .0145851{col 41}{space 1}    0.39{col 50}{space 3}0.697{col 58}{space 4}-.0229571{col 71}{space 3} .0343045
{txt}{space 7}townfe_11 {c |}{col 18}{res}{space 2} .0112722{col 30}{space 2} .0140355{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4}-.0162798{col 71}{space 3} .0388243
{txt}{space 7}townfe_12 {c |}{col 18}{res}{space 2} .0057304{col 30}{space 2} .0154923{col 41}{space 1}    0.37{col 50}{space 3}0.712{col 58}{space 4}-.0246813{col 71}{space 3} .0361421
{txt}{space 7}townfe_13 {c |}{col 18}{res}{space 2} .0151926{col 30}{space 2} .0151684{col 41}{space 1}    1.00{col 50}{space 3}0.317{col 58}{space 4}-.0145832{col 71}{space 3} .0449684
{txt}{space 7}townfe_14 {c |}{col 18}{res}{space 2} .0148988{col 30}{space 2} .0147249{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.0140065{col 71}{space 3} .0438042
{txt}{space 7}townfe_15 {c |}{col 18}{res}{space 2}-.0048492{col 30}{space 2} .0126664{col 41}{space 1}   -0.38{col 50}{space 3}0.702{col 58}{space 4}-.0297135{col 71}{space 3} .0200151
{txt}{space 7}townfe_16 {c |}{col 18}{res}{space 2} .0006516{col 30}{space 2} .0126851{col 41}{space 1}    0.05{col 50}{space 3}0.959{col 58}{space 4}-.0242494{col 71}{space 3} .0255527
{txt}{space 7}townfe_17 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 7}townfe_18 {c |}{col 18}{res}{space 2} .0181561{col 30}{space 2} .0155649{col 41}{space 1}    1.17{col 50}{space 3}0.244{col 58}{space 4}-.0123982{col 71}{space 3} .0487105
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3593282{col 30}{space 2} .0416498{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .2775688{col 71}{space 3} .4410877
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/interactions", replace side tex(frag) bdec(3) drop(e_* $townfe) ctitle(All)       label   
{txt}{stata `"shellout using `"Tables/interactions.tex"'"':Tables/interactions.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/interactions.txt", label"':seeout}

{com}. 
.         reg rank elect local tax transfer kinvill buyel water health educ infra $interacts $fe $townfe, cluster(pid)
{txt}note: e_2 omitted because of collinearity
note: townfe_5 omitted because of collinearity
note: townfe_17 omitted because of collinearity

Linear regression                                      Number of obs ={res}    6224
                                                       {txt}F( 72,   777) ={res}   24.05
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1991
                                                       {txt}Root MSE      = {res}   .811

{txt}{ralign 82:(Std. Err. adjusted for {res:778} clusters in pid)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            rank{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}elect {c |}{col 18}{res}{space 2} .1432384{col 30}{space 2} .0650443{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0155549{col 71}{space 3} .2709218
{txt}{space 11}local {c |}{col 18}{res}{space 2} .0290739{col 30}{space 2} .0659061{col 41}{space 1}    0.44{col 50}{space 3}0.659{col 58}{space 4}-.1003013{col 71}{space 3} .1584491
{txt}{space 13}tax {c |}{col 18}{res}{space 2} .2661924{col 30}{space 2} .0791795{col 41}{space 1}    3.36{col 50}{space 3}0.001{col 58}{space 4} .1107612{col 71}{space 3} .4216235
{txt}{space 8}transfer {c |}{col 18}{res}{space 2} .0636856{col 30}{space 2} .0753914{col 41}{space 1}    0.84{col 50}{space 3}0.399{col 58}{space 4}-.0843094{col 71}{space 3} .2116806
{txt}{space 9}kinvill {c |}{col 18}{res}{space 2}-.3572463{col 30}{space 2} .0775835{col 41}{space 1}   -4.60{col 50}{space 3}0.000{col 58}{space 4}-.5095444{col 71}{space 3}-.2049482
{txt}{space 11}buyel {c |}{col 18}{res}{space 2}-.1966087{col 30}{space 2} .0768639{col 41}{space 1}   -2.56{col 50}{space 3}0.011{col 58}{space 4}-.3474942{col 71}{space 3}-.0457233
{txt}{space 11}water {c |}{col 18}{res}{space 2} .1891801{col 30}{space 2} .0942417{col 41}{space 1}    2.01{col 50}{space 3}0.045{col 58}{space 4} .0041816{col 71}{space 3} .3741785
{txt}{space 10}health {c |}{col 18}{res}{space 2}  .452544{col 30}{space 2} .0868552{col 41}{space 1}    5.21{col 50}{space 3}0.000{col 58}{space 4} .2820453{col 71}{space 3} .6230427
{txt}{space 12}educ {c |}{col 18}{res}{space 2} .3536905{col 30}{space 2} .0879227{col 41}{space 1}    4.02{col 50}{space 3}0.000{col 58}{space 4} .1810963{col 71}{space 3} .5262846
{txt}{space 11}infra {c |}{col 18}{res}{space 2}  .173779{col 30}{space 2} .0835195{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0098283{col 71}{space 3} .3377296
{txt}{space 5}elect_local {c |}{col 18}{res}{space 2}-.0448236{col 30}{space 2} .0425142{col 41}{space 1}   -1.05{col 50}{space 3}0.292{col 58}{space 4}-.1282799{col 71}{space 3} .0386327
{txt}{space 7}elect_tax {c |}{col 18}{res}{space 2}-.0112077{col 30}{space 2} .0491655{col 41}{space 1}   -0.23{col 50}{space 3}0.820{col 58}{space 4}-.1077207{col 71}{space 3} .0853053
{txt}{space 2}elect_transfer {c |}{col 18}{res}{space 2} .0278271{col 30}{space 2} .0516405{col 41}{space 1}    0.54{col 50}{space 3}0.590{col 58}{space 4}-.0735444{col 71}{space 3} .1291986
{txt}{space 3}elect_kinvill {c |}{col 18}{res}{space 2} .0733828{col 30}{space 2} .0503066{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0253702{col 71}{space 3} .1721358
{txt}{space 5}elect_buyel {c |}{col 18}{res}{space 2}-.0378466{col 30}{space 2} .0488064{col 41}{space 1}   -0.78{col 50}{space 3}0.438{col 58}{space 4}-.1336547{col 71}{space 3} .0579614
{txt}{space 5}elect_water {c |}{col 18}{res}{space 2}-.0016246{col 30}{space 2} .0671521{col 41}{space 1}   -0.02{col 50}{space 3}0.981{col 58}{space 4}-.1334456{col 71}{space 3} .1301963
{txt}{space 4}elect_health {c |}{col 18}{res}{space 2}-.0306619{col 30}{space 2} .0670905{col 41}{space 1}   -0.46{col 50}{space 3}0.648{col 58}{space 4}-.1623619{col 71}{space 3} .1010382
{txt}{space 6}elect_educ {c |}{col 18}{res}{space 2} .0322223{col 30}{space 2} .0661312{col 41}{space 1}    0.49{col 50}{space 3}0.626{col 58}{space 4}-.0975947{col 71}{space 3} .1620392
{txt}{space 5}elect_infra {c |}{col 18}{res}{space 2}-.0480824{col 30}{space 2} .0643405{col 41}{space 1}   -0.75{col 50}{space 3}0.455{col 58}{space 4}-.1743842{col 71}{space 3} .0782194
{txt}{space 7}local_tax {c |}{col 18}{res}{space 2}  .025862{col 30}{space 2} .0513726{col 41}{space 1}    0.50{col 50}{space 3}0.615{col 58}{space 4}-.0749835{col 71}{space 3} .1267075
{txt}{space 2}local_transfer {c |}{col 18}{res}{space 2} .0013057{col 30}{space 2} .0509713{col 41}{space 1}    0.03{col 50}{space 3}0.980{col 58}{space 4}-.0987521{col 71}{space 3} .1013635
{txt}{space 3}local_kinvill {c |}{col 18}{res}{space 2}-.0606428{col 30}{space 2} .0521121{col 41}{space 1}   -1.16{col 50}{space 3}0.245{col 58}{space 4}-.1629401{col 71}{space 3} .0416545
{txt}{space 5}local_buyel {c |}{col 18}{res}{space 2}-.0328596{col 30}{space 2} .0492503{col 41}{space 1}   -0.67{col 50}{space 3}0.505{col 58}{space 4}-.1295391{col 71}{space 3} .0638198
{txt}{space 5}local_water {c |}{col 18}{res}{space 2}-.0266869{col 30}{space 2}  .068648{col 41}{space 1}   -0.39{col 50}{space 3}0.698{col 58}{space 4}-.1614444{col 71}{space 3} .1080706
{txt}{space 4}local_health {c |}{col 18}{res}{space 2}-.0083714{col 30}{space 2} .0669998{col 41}{space 1}   -0.12{col 50}{space 3}0.901{col 58}{space 4}-.1398935{col 71}{space 3} .1231507
{txt}{space 6}local_educ {c |}{col 18}{res}{space 2}-.0459157{col 30}{space 2} .0651691{col 41}{space 1}   -0.70{col 50}{space 3}0.481{col 58}{space 4} -.173844{col 71}{space 3} .0820126
{txt}{space 5}local_infra {c |}{col 18}{res}{space 2} .0995815{col 30}{space 2} .0652405{col 41}{space 1}    1.53{col 50}{space 3}0.127{col 58}{space 4}-.0284869{col 71}{space 3}   .22765
{txt}{space 5}tax_kinvill {c |}{col 18}{res}{space 2}  .008401{col 30}{space 2}  .063116{col 41}{space 1}    0.13{col 50}{space 3}0.894{col 58}{space 4} -.115497{col 71}{space 3} .1322991
{txt}{space 7}tax_buyel {c |}{col 18}{res}{space 2} .0402962{col 30}{space 2}  .057186{col 41}{space 1}    0.70{col 50}{space 3}0.481{col 58}{space 4}-.0719612{col 71}{space 3} .1525536
{txt}{space 7}tax_water {c |}{col 18}{res}{space 2} .0533414{col 30}{space 2} .0860339{col 41}{space 1}    0.62{col 50}{space 3}0.535{col 58}{space 4}-.1155449{col 71}{space 3} .2222277
{txt}{space 6}tax_health {c |}{col 18}{res}{space 2}-.0603928{col 30}{space 2} .0806657{col 41}{space 1}   -0.75{col 50}{space 3}0.454{col 58}{space 4}-.2187414{col 71}{space 3} .0979558
{txt}{space 8}tax_educ {c |}{col 18}{res}{space 2}  .008021{col 30}{space 2} .0774226{col 41}{space 1}    0.10{col 50}{space 3}0.918{col 58}{space 4}-.1439614{col 71}{space 3} .1600033
{txt}{space 7}tax_infra {c |}{col 18}{res}{space 2} .0707966{col 30}{space 2} .0823788{col 41}{space 1}    0.86{col 50}{space 3}0.390{col 58}{space 4}-.0909148{col 71}{space 3} .2325079
{txt}transfer_kinvill {c |}{col 18}{res}{space 2} .0111646{col 30}{space 2} .0656197{col 41}{space 1}    0.17{col 50}{space 3}0.865{col 58}{space 4}-.1176483{col 71}{space 3} .1399775
{txt}{space 2}transfer_buyel {c |}{col 18}{res}{space 2} .0235043{col 30}{space 2} .0615232{col 41}{space 1}    0.38{col 50}{space 3}0.703{col 58}{space 4}-.0972672{col 71}{space 3} .1442758
{txt}{space 2}transfer_water {c |}{col 18}{res}{space 2}-.0474647{col 30}{space 2} .0875385{col 41}{space 1}   -0.54{col 50}{space 3}0.588{col 58}{space 4}-.2193048{col 71}{space 3} .1243753
{txt}{space 1}transfer_health {c |}{col 18}{res}{space 2}-.0479415{col 30}{space 2} .0807199{col 41}{space 1}   -0.59{col 50}{space 3}0.553{col 58}{space 4}-.2063964{col 71}{space 3} .1105133
{txt}{space 3}transfer_educ {c |}{col 18}{res}{space 2} .0069645{col 30}{space 2} .0791896{col 41}{space 1}    0.09{col 50}{space 3}0.930{col 58}{space 4}-.1484864{col 71}{space 3} .1624153
{txt}{space 2}transfer_infra {c |}{col 18}{res}{space 2}-.0094542{col 30}{space 2} .0820992{col 41}{space 1}   -0.12{col 50}{space 3}0.908{col 58}{space 4}-.1706168{col 71}{space 3} .1517084
{txt}{space 3}kinvill_water {c |}{col 18}{res}{space 2} .0195525{col 30}{space 2}  .081458{col 41}{space 1}    0.24{col 50}{space 3}0.810{col 58}{space 4}-.1403513{col 71}{space 3} .1794563
{txt}{space 2}kinvill_health {c |}{col 18}{res}{space 2}  .089079{col 30}{space 2} .0792013{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}-.0663948{col 71}{space 3} .2445528
{txt}{space 4}kinvill_educ {c |}{col 18}{res}{space 2}-.0505233{col 30}{space 2} .0818439{col 41}{space 1}   -0.62{col 50}{space 3}0.537{col 58}{space 4}-.2111847{col 71}{space 3} .1101382
{txt}{space 3}kinvill_infra {c |}{col 18}{res}{space 2} .0106972{col 30}{space 2} .0798031{col 41}{space 1}    0.13{col 50}{space 3}0.893{col 58}{space 4} -.145958{col 71}{space 3} .1673525
{txt}{space 5}buyel_water {c |}{col 18}{res}{space 2}-.0212991{col 30}{space 2} .0824929{col 41}{space 1}   -0.26{col 50}{space 3}0.796{col 58}{space 4}-.1832344{col 71}{space 3} .1406362
{txt}{space 4}buyel_health {c |}{col 18}{res}{space 2} .0500468{col 30}{space 2} .0810534{col 41}{space 1}    0.62{col 50}{space 3}0.537{col 58}{space 4}-.1090628{col 71}{space 3} .2091565
{txt}{space 6}buyel_educ {c |}{col 18}{res}{space 2}-.0922981{col 30}{space 2} .0789699{col 41}{space 1}   -1.17{col 50}{space 3}0.243{col 58}{space 4}-.2473177{col 71}{space 3} .0627215
{txt}{space 5}buyel_infra {c |}{col 18}{res}{space 2} .0338859{col 30}{space 2} .0812342{col 41}{space 1}    0.42{col 50}{space 3}0.677{col 58}{space 4}-.1255787{col 71}{space 3} .1933505
{txt}{space 13}e_1 {c |}{col 18}{res}{space 2} .3607862{col 30}{space 2}  .111455{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .1419977{col 71}{space 3} .5795747
{txt}{space 13}e_2 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 13}e_3 {c |}{col 18}{res}{space 2}-.1955363{col 30}{space 2} .1067562{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.4051011{col 71}{space 3} .0140285
{txt}{space 13}e_4 {c |}{col 18}{res}{space 2} .1135603{col 30}{space 2} .1079376{col 41}{space 1}    1.05{col 50}{space 3}0.293{col 58}{space 4}-.0983235{col 71}{space 3} .3254441
{txt}{space 13}e_5 {c |}{col 18}{res}{space 2} .3039311{col 30}{space 2} .1039642{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .0998471{col 71}{space 3} .5080151
{txt}{space 13}e_6 {c |}{col 18}{res}{space 2} .7104421{col 30}{space 2} .0664285{col 41}{space 1}   10.69{col 50}{space 3}0.000{col 58}{space 4} .5800414{col 71}{space 3} .8408428
{txt}{space 13}e_7 {c |}{col 18}{res}{space 2} .0189663{col 30}{space 2} .0683132{col 41}{space 1}    0.28{col 50}{space 3}0.781{col 58}{space 4} -.115134{col 71}{space 3} .1530667
{txt}{space 13}e_8 {c |}{col 18}{res}{space 2}-.1776511{col 30}{space 2}  .064536{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.3043367{col 71}{space 3}-.0509656
{txt}{space 13}e_9 {c |}{col 18}{res}{space 2} .7124737{col 30}{space 2} .0650263{col 41}{space 1}   10.96{col 50}{space 3}0.000{col 58}{space 4} .5848256{col 71}{space 3} .8401219
{txt}{space 12}e_10 {c |}{col 18}{res}{space 2} .0224423{col 30}{space 2} .1047566{col 41}{space 1}    0.21{col 50}{space 3}0.830{col 58}{space 4}-.1831972{col 71}{space 3} .2280819
{txt}{space 8}townfe_1 {c |}{col 18}{res}{space 2} -.097077{col 30}{space 2} .0887582{col 41}{space 1}   -1.09{col 50}{space 3}0.274{col 58}{space 4}-.2713112{col 71}{space 3} .0771573
{txt}{space 8}townfe_2 {c |}{col 18}{res}{space 2} .0503274{col 30}{space 2} .0869838{col 41}{space 1}    0.58{col 50}{space 3}0.563{col 58}{space 4}-.1204237{col 71}{space 3} .2210784
{txt}{space 8}townfe_3 {c |}{col 18}{res}{space 2}  -.05845{col 30}{space 2} .0850733{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.2254507{col 71}{space 3} .1085507
{txt}{space 8}townfe_4 {c |}{col 18}{res}{space 2}-.1553313{col 30}{space 2} .0713754{col 41}{space 1}   -2.18{col 50}{space 3}0.030{col 58}{space 4}-.2954428{col 71}{space 3}-.0152199
{txt}{space 8}townfe_5 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 8}townfe_6 {c |}{col 18}{res}{space 2}-.2241295{col 30}{space 2} .0674562{col 41}{space 1}   -3.32{col 50}{space 3}0.001{col 58}{space 4}-.3565475{col 71}{space 3}-.0917115
{txt}{space 8}townfe_7 {c |}{col 18}{res}{space 2}-.1570092{col 30}{space 2} .0723293{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.2989933{col 71}{space 3}-.0150251
{txt}{space 8}townfe_8 {c |}{col 18}{res}{space 2}-.1218838{col 30}{space 2} .0696513{col 41}{space 1}   -1.75{col 50}{space 3}0.081{col 58}{space 4}-.2586107{col 71}{space 3} .0148431
{txt}{space 8}townfe_9 {c |}{col 18}{res}{space 2} -.105557{col 30}{space 2} .0606267{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-.2245684{col 71}{space 3} .0134545
{txt}{space 7}townfe_10 {c |}{col 18}{res}{space 2}-.0209046{col 30}{space 2} .0872563{col 41}{space 1}   -0.24{col 50}{space 3}0.811{col 58}{space 4}-.1921907{col 71}{space 3} .1503814
{txt}{space 7}townfe_11 {c |}{col 18}{res}{space 2}-.1019629{col 30}{space 2} .0796961{col 41}{space 1}   -1.28{col 50}{space 3}0.201{col 58}{space 4}-.2584082{col 71}{space 3} .0544824
{txt}{space 7}townfe_12 {c |}{col 18}{res}{space 2} .1070502{col 30}{space 2} .0879608{col 41}{space 1}    1.22{col 50}{space 3}0.224{col 58}{space 4}-.0656188{col 71}{space 3} .2797191
{txt}{space 7}townfe_13 {c |}{col 18}{res}{space 2} .1494438{col 30}{space 2}   .08593{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0192387{col 71}{space 3} .3181262
{txt}{space 7}townfe_14 {c |}{col 18}{res}{space 2} .0337791{col 30}{space 2}  .086832{col 41}{space 1}    0.39{col 50}{space 3}0.697{col 58}{space 4}-.1366741{col 71}{space 3} .2042323
{txt}{space 7}townfe_15 {c |}{col 18}{res}{space 2}-.0679994{col 30}{space 2} .0604565{col 41}{space 1}   -1.12{col 50}{space 3}0.261{col 58}{space 4}-.1866769{col 71}{space 3}  .050678
{txt}{space 7}townfe_16 {c |}{col 18}{res}{space 2}-.0322255{col 30}{space 2} .0592614{col 41}{space 1}   -0.54{col 50}{space 3}0.587{col 58}{space 4}-.1485568{col 71}{space 3} .0841059
{txt}{space 7}townfe_17 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 7}townfe_18 {c |}{col 18}{res}{space 2} .0289497{col 30}{space 2} .0862014{col 41}{space 1}    0.34{col 50}{space 3}0.737{col 58}{space 4}-.1402655{col 71}{space 3} .1981649
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.683205{col 30}{space 2} .0975226{col 41}{space 1}   37.77{col 50}{space 3}0.000{col 58}{space 4} 3.491766{col 71}{space 3} 3.874644
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 outreg2 using "Tables/interactions", append side tex(frag) bdec(3) drop(e_* $townfe) ctitle(Rank)       label   
{txt}{stata `"shellout using `"Tables/interactions.tex"'"':Tables/interactions.tex}
{browse `"/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files"' :dir}{com} : {txt}{stata `"seeout using "Tables/interactions.txt", label"':seeout}

{com}. 
.                 
.                 
. ********        APPENDIX C6: HETEROGENEITY ANALYSIS
. 
. 
. // FIGURE 5: Results by whether thought last elections were free & fair & by party membership
. 
.         ** LEFT-HAND SIDE: Heterogeneity by whether thought last elections free & fair
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if freefair==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2152
                                                       {txt}F( 35,   268) ={res}   13.47
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1258
                                                       {txt}Root MSE      = {res} .47144

{txt}{ralign 87:(Std. Err. adjusted for {res:269} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1376828{col 35}{space 2} .0244673{col 46}{space 1}    5.63{col 55}{space 3}0.000{col 63}{space 4} .0895101{col 76}{space 3} .1858554
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0050113{col 35}{space 2} .0204937{col 46}{space 1}    0.24{col 55}{space 3}0.807{col 63}{space 4}-.0353378{col 76}{space 3} .0453603
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.2134494{col 35}{space 2} .0272117{col 46}{space 1}   -7.84{col 55}{space 3}0.000{col 63}{space 4}-.2670253{col 76}{space 3}-.1598734
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2392632{col 35}{space 2} .0263564{col 46}{space 1}   -9.08{col 55}{space 3}0.000{col 63}{space 4}-.2911551{col 76}{space 3}-.1873713
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0678072{col 35}{space 2} .0349851{col 46}{space 1}    1.94{col 55}{space 3}0.054{col 63}{space 4}-.0010735{col 76}{space 3} .1366878
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0748733{col 35}{space 2} .0360318{col 46}{space 1}    2.08{col 55}{space 3}0.039{col 63}{space 4} .0039319{col 76}{space 3} .1458148
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1267317{col 35}{space 2} .0349717{col 46}{space 1}    3.62{col 55}{space 3}0.000{col 63}{space 4} .0578774{col 76}{space 3} .1955859
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2163229{col 35}{space 2} .0326058{col 46}{space 1}    6.63{col 55}{space 3}0.000{col 63}{space 4} .1521269{col 76}{space 3} .2805189
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2507553{col 35}{space 2} .0258551{col 46}{space 1}    9.70{col 55}{space 3}0.000{col 63}{space 4} .1998504{col 76}{space 3} .3016601
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0804612{col 35}{space 2} .0274977{col 46}{space 1}    2.93{col 55}{space 3}0.004{col 63}{space 4} .0263221{col 76}{space 3} .1346002
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0143064{col 35}{space 2} .0251264{col 46}{space 1}   -0.57{col 55}{space 3}0.570{col 63}{space 4}-.0637766{col 76}{space 3} .0351638
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0155159{col 35}{space 2} .0277987{col 46}{space 1}   -0.56{col 55}{space 3}0.577{col 63}{space 4}-.0702475{col 76}{space 3} .0392157
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0208293{col 35}{space 2} .0157941{col 46}{space 1}   -1.32{col 55}{space 3}0.188{col 63}{space 4}-.0519256{col 76}{space 3} .0102671
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0034726{col 35}{space 2} .0217262{col 46}{space 1}    0.16{col 55}{space 3}0.873{col 63}{space 4}-.0393031{col 76}{space 3} .0462484
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0012843{col 35}{space 2}  .015752{col 46}{space 1}   -0.08{col 55}{space 3}0.935{col 63}{space 4}-.0322976{col 76}{space 3} .0297291
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0166075{col 35}{space 2} .0253294{col 46}{space 1}   -0.66{col 55}{space 3}0.513{col 63}{space 4}-.0664773{col 76}{space 3} .0332624
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0279385{col 35}{space 2} .0293577{col 46}{space 1}   -0.95{col 55}{space 3}0.342{col 63}{space 4}-.0857396{col 76}{space 3} .0298626
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0244534{col 35}{space 2} .0260741{col 46}{space 1}   -0.94{col 55}{space 3}0.349{col 63}{space 4}-.0757895{col 76}{space 3} .0268826
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0024427{col 35}{space 2} .0336963{col 46}{space 1}   -0.07{col 55}{space 3}0.942{col 63}{space 4}-.0687859{col 76}{space 3} .0639004
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0164169{col 35}{space 2} .0233525{col 46}{space 1}   -0.70{col 55}{space 3}0.483{col 63}{space 4}-.0623946{col 76}{space 3} .0295608
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2}-.0061062{col 35}{space 2}  .021077{col 46}{space 1}   -0.29{col 55}{space 3}0.772{col 63}{space 4}-.0476037{col 76}{space 3} .0353913
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0308362{col 35}{space 2} .0209938{col 46}{space 1}   -1.47{col 55}{space 3}0.143{col 63}{space 4}  -.07217{col 76}{space 3} .0104976
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0096159{col 35}{space 2} .0259116{col 46}{space 1}    0.37{col 55}{space 3}0.711{col 63}{space 4}-.0414004{col 76}{space 3} .0606321
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0423508{col 35}{space 2} .0347472{col 46}{space 1}   -1.22{col 55}{space 3}0.224{col 63}{space 4} -.110763{col 76}{space 3} .0260613
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0006231{col 35}{space 2} .0214277{col 46}{space 1}   -0.03{col 55}{space 3}0.977{col 63}{space 4}-.0428112{col 76}{space 3} .0415649
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2} .0010561{col 35}{space 2} .0226216{col 46}{space 1}    0.05{col 55}{space 3}0.963{col 63}{space 4}-.0434826{col 76}{space 3} .0455949
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2}-.0065596{col 35}{space 2} .0241348{col 46}{space 1}   -0.27{col 55}{space 3}0.786{col 63}{space 4}-.0540775{col 76}{space 3} .0409584
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0085668{col 35}{space 2} .0212915{col 46}{space 1}    0.40{col 55}{space 3}0.688{col 63}{space 4} -.033353{col 76}{space 3} .0504866
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2} -.007071{col 35}{space 2} .0197742{col 46}{space 1}   -0.36{col 55}{space 3}0.721{col 63}{space 4}-.0460036{col 76}{space 3} .0318615
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}-.0112913{col 35}{space 2} .0245699{col 46}{space 1}   -0.46{col 55}{space 3}0.646{col 63}{space 4}-.0596659{col 76}{space 3} .0370833
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0148797{col 35}{space 2} .0232123{col 46}{space 1}   -0.64{col 55}{space 3}0.522{col 63}{space 4}-.0605813{col 76}{space 3} .0308219
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0069122{col 35}{space 2}  .019249{col 46}{space 1}   -0.36{col 55}{space 3}0.720{col 63}{space 4}-.0448106{col 76}{space 3} .0309863
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0046863{col 35}{space 2} .0191853{col 46}{space 1}    0.24{col 55}{space 3}0.807{col 63}{space 4}-.0330868{col 76}{space 3} .0424594
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0069532{col 35}{space 2}   .02277{col 46}{space 1}   -0.31{col 55}{space 3}0.760{col 63}{space 4}-.0517841{col 76}{space 3} .0378776
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0064448{col 35}{space 2} .0252565{col 46}{space 1}    0.26{col 55}{space 3}0.799{col 63}{space 4}-.0432815{col 76}{space 3} .0561712
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3995882{col 35}{space 2} .0407753{col 46}{space 1}    9.80{col 55}{space 3}0.000{col 63}{space 4} .3193074{col 76}{space 3} .4798689
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_freefair
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if freefair==0, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    4072
                                                       {txt}F( 35,   508) ={res}   11.75
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0857
                                                       {txt}Root MSE      = {res} .48023

{txt}{ralign 87:(Std. Err. adjusted for {res:509} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0775811{col 35}{space 2} .0166877{col 46}{space 1}    4.65{col 55}{space 3}0.000{col 63}{space 4} .0447957{col 76}{space 3} .1103666
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0237674{col 35}{space 2} .0157407{col 46}{space 1}    1.51{col 55}{space 3}0.132{col 63}{space 4}-.0071575{col 76}{space 3} .0546923
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1089307{col 35}{space 2} .0193105{col 46}{space 1}   -5.64{col 55}{space 3}0.000{col 63}{space 4} -.146869{col 76}{space 3}-.0709924
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1755239{col 35}{space 2} .0190757{col 46}{space 1}   -9.20{col 55}{space 3}0.000{col 63}{space 4}-.2130008{col 76}{space 3} -.138047
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0935004{col 35}{space 2} .0257601{col 46}{space 1}    3.63{col 55}{space 3}0.000{col 63}{space 4} .0428909{col 76}{space 3} .1441099
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0933298{col 35}{space 2} .0242786{col 46}{space 1}    3.84{col 55}{space 3}0.000{col 63}{space 4} .0456309{col 76}{space 3} .1410287
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1346923{col 35}{space 2} .0241896{col 46}{space 1}    5.57{col 55}{space 3}0.000{col 63}{space 4} .0871683{col 76}{space 3} .1822163
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2649606{col 35}{space 2} .0257394{col 46}{space 1}   10.29{col 55}{space 3}0.000{col 63}{space 4} .2143919{col 76}{space 3} .3155294
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .1847034{col 35}{space 2} .0209295{col 46}{space 1}    8.83{col 55}{space 3}0.000{col 63}{space 4} .1435844{col 76}{space 3} .2258223
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0040688{col 35}{space 2} .0196642{col 46}{space 1}    0.21{col 55}{space 3}0.836{col 63}{space 4}-.0345644{col 76}{space 3}  .042702
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0035971{col 35}{space 2}  .008761{col 46}{space 1}   -0.41{col 55}{space 3}0.682{col 63}{space 4}-.0208094{col 76}{space 3} .0136151
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0090426{col 35}{space 2} .0187007{col 46}{space 1}   -0.48{col 55}{space 3}0.629{col 63}{space 4}-.0457828{col 76}{space 3} .0276977
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0205141{col 35}{space 2} .0107485{col 46}{space 1}   -1.91{col 55}{space 3}0.057{col 63}{space 4}-.0416312{col 76}{space 3} .0006029
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0019912{col 35}{space 2} .0111353{col 46}{space 1}    0.18{col 55}{space 3}0.858{col 63}{space 4}-.0198856{col 76}{space 3}  .023868
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0052835{col 35}{space 2} .0108318{col 46}{space 1}    0.49{col 55}{space 3}0.626{col 63}{space 4}-.0159971{col 76}{space 3}  .026564
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0147335{col 35}{space 2} .0184648{col 46}{space 1}   -0.80{col 55}{space 3}0.425{col 63}{space 4}-.0510103{col 76}{space 3} .0215434
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0113465{col 35}{space 2}  .017887{col 46}{space 1}   -0.63{col 55}{space 3}0.526{col 63}{space 4}-.0464881{col 76}{space 3} .0237951
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0168476{col 35}{space 2} .0211941{col 46}{space 1}   -0.79{col 55}{space 3}0.427{col 63}{space 4}-.0584865{col 76}{space 3} .0247912
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0053455{col 35}{space 2} .0179416{col 46}{space 1}   -0.30{col 55}{space 3}0.766{col 63}{space 4}-.0405944{col 76}{space 3} .0299034
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0202833{col 35}{space 2} .0141434{col 46}{space 1}   -1.43{col 55}{space 3}0.152{col 63}{space 4}-.0480701{col 76}{space 3} .0075035
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0072348{col 35}{space 2} .0144586{col 46}{space 1}    0.50{col 55}{space 3}0.617{col 63}{space 4}-.0211713{col 76}{space 3} .0356408
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2} -.013358{col 35}{space 2} .0129174{col 46}{space 1}   -1.03{col 55}{space 3}0.302{col 63}{space 4}-.0387361{col 76}{space 3} .0120202
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0109378{col 35}{space 2} .0152854{col 46}{space 1}    0.72{col 55}{space 3}0.475{col 63}{space 4}-.0190925{col 76}{space 3} .0409681
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0101622{col 35}{space 2} .0153548{col 46}{space 1}   -0.66{col 55}{space 3}0.508{col 63}{space 4}-.0403289{col 76}{space 3} .0200044
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0099034{col 35}{space 2} .0166549{col 46}{space 1}   -0.59{col 55}{space 3}0.552{col 63}{space 4}-.0426242{col 76}{space 3} .0228175
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0002843{col 35}{space 2} .0156433{col 46}{space 1}   -0.02{col 55}{space 3}0.986{col 63}{space 4}-.0310179{col 76}{space 3} .0304493
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0209793{col 35}{space 2} .0152012{col 46}{space 1}    1.38{col 55}{space 3}0.168{col 63}{space 4}-.0088856{col 76}{space 3} .0508443
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0052293{col 35}{space 2} .0170676{col 46}{space 1}   -0.31{col 55}{space 3}0.759{col 63}{space 4}-.0387612{col 76}{space 3} .0283026
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0125619{col 35}{space 2} .0135603{col 46}{space 1}   -0.93{col 55}{space 3}0.355{col 63}{space 4}-.0392031{col 76}{space 3} .0140792
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0180412{col 35}{space 2} .0173373{col 46}{space 1}    1.04{col 55}{space 3}0.299{col 63}{space 4}-.0160205{col 76}{space 3} .0521029
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0044757{col 35}{space 2} .0143653{col 46}{space 1}   -0.31{col 55}{space 3}0.756{col 63}{space 4}-.0326983{col 76}{space 3}  .023747
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0001546{col 35}{space 2} .0156322{col 46}{space 1}    0.01{col 55}{space 3}0.992{col 63}{space 4}-.0305571{col 76}{space 3} .0308662
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} -.006675{col 35}{space 2} .0137257{col 46}{space 1}   -0.49{col 55}{space 3}0.627{col 63}{space 4} -.033641{col 76}{space 3} .0202911
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0008606{col 35}{space 2} .0159235{col 46}{space 1}   -0.05{col 55}{space 3}0.957{col 63}{space 4}-.0321445{col 76}{space 3} .0304234
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0086664{col 35}{space 2} .0158131{col 46}{space 1}    0.55{col 55}{space 3}0.584{col 63}{space 4}-.0224007{col 76}{space 3} .0397335
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3714408{col 35}{space 2}  .028604{col 46}{space 1}   12.99{col 55}{space 3}0.000{col 63}{space 4}  .315244{col 76}{space 3} .4276375
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_nofreefair
{txt}
{com}.                 
.         coefplot (chosen_freefair, label(Elections were Free and Fair) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_nofreefair, label(Elections not Free and Fair) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_freefair.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_freefair.pdf written in PDF format)

{com}. 
.                                 
.         ** RIGHT-HAND SIDE: Heterogeneity by whether belong to any political party
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if polparty==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2040
                                                       {txt}F( 35,   254) ={res}   10.91
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1258
                                                       {txt}Root MSE      = {res} .47168

{txt}{ralign 87:(Std. Err. adjusted for {res:255} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1580728{col 35}{space 2} .0237327{col 46}{space 1}    6.66{col 55}{space 3}0.000{col 63}{space 4} .1113349{col 76}{space 3} .2048107
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0412918{col 35}{space 2} .0218649{col 46}{space 1}    1.89{col 55}{space 3}0.060{col 63}{space 4}-.0017678{col 76}{space 3} .0843514
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1739804{col 35}{space 2} .0270711{col 46}{space 1}   -6.43{col 55}{space 3}0.000{col 63}{space 4}-.2272928{col 76}{space 3} -.120668
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2194937{col 35}{space 2} .0281664{col 46}{space 1}   -7.79{col 55}{space 3}0.000{col 63}{space 4}-.2749631{col 76}{space 3}-.1640243
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0453945{col 35}{space 2} .0354076{col 46}{space 1}    1.28{col 55}{space 3}0.201{col 63}{space 4}-.0243354{col 76}{space 3} .1151244
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0656615{col 35}{space 2} .0350278{col 46}{space 1}    1.87{col 55}{space 3}0.062{col 63}{space 4}-.0033205{col 76}{space 3} .1346435
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .087245{col 35}{space 2} .0351247{col 46}{space 1}    2.48{col 55}{space 3}0.014{col 63}{space 4} .0180723{col 76}{space 3} .1564177
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2330233{col 35}{space 2} .0359336{col 46}{space 1}    6.48{col 55}{space 3}0.000{col 63}{space 4} .1622575{col 76}{space 3}  .303789
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2157906{col 35}{space 2} .0274972{col 46}{space 1}    7.85{col 55}{space 3}0.000{col 63}{space 4}  .161639{col 76}{space 3} .2699422
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0070378{col 35}{space 2} .0282436{col 46}{space 1}    0.25{col 55}{space 3}0.803{col 63}{space 4}-.0485837{col 76}{space 3} .0626593
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2} -.042512{col 35}{space 2} .0203475{col 46}{space 1}   -2.09{col 55}{space 3}0.038{col 63}{space 4}-.0825832{col 76}{space 3}-.0024408
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2} .0068131{col 35}{space 2} .0281503{col 46}{space 1}    0.24{col 55}{space 3}0.809{col 63}{space 4}-.0486246{col 76}{space 3} .0622508
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0181683{col 35}{space 2} .0137164{col 46}{space 1}   -1.32{col 55}{space 3}0.187{col 63}{space 4}-.0451807{col 76}{space 3} .0088442
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0035352{col 35}{space 2} .0152483{col 46}{space 1}   -0.23{col 55}{space 3}0.817{col 63}{space 4}-.0335645{col 76}{space 3} .0264941
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}  .016732{col 35}{space 2} .0185205{col 46}{space 1}    0.90{col 55}{space 3}0.367{col 63}{space 4}-.0197413{col 76}{space 3} .0532053
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0146729{col 35}{space 2} .0303476{col 46}{space 1}   -0.48{col 55}{space 3}0.629{col 63}{space 4}-.0744378{col 76}{space 3} .0450921
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0131638{col 35}{space 2} .0228818{col 46}{space 1}   -0.58{col 55}{space 3}0.566{col 63}{space 4}-.0582259{col 76}{space 3} .0318984
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0094102{col 35}{space 2} .0242988{col 46}{space 1}   -0.39{col 55}{space 3}0.699{col 63}{space 4}-.0572629{col 76}{space 3} .0384425
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2} .0321045{col 35}{space 2} .0271699{col 46}{space 1}    1.18{col 55}{space 3}0.238{col 63}{space 4}-.0214024{col 76}{space 3} .0856115
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}  -.00968{col 35}{space 2} .0241062{col 46}{space 1}   -0.40{col 55}{space 3}0.688{col 63}{space 4}-.0571534{col 76}{space 3} .0377935
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0001114{col 35}{space 2} .0184163{col 46}{space 1}    0.01{col 55}{space 3}0.995{col 63}{space 4}-.0361568{col 76}{space 3} .0363796
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2} -.004869{col 35}{space 2}  .020038{col 46}{space 1}   -0.24{col 55}{space 3}0.808{col 63}{space 4}-.0443307{col 76}{space 3} .0345927
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.0078537{col 35}{space 2} .0282583{col 46}{space 1}   -0.28{col 55}{space 3}0.781{col 63}{space 4} -.063504{col 76}{space 3} .0477966
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0041057{col 35}{space 2} .0342117{col 46}{space 1}   -0.12{col 55}{space 3}0.905{col 63}{space 4}-.0714805{col 76}{space 3} .0632691
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0015567{col 35}{space 2} .0281323{col 46}{space 1}   -0.06{col 55}{space 3}0.956{col 63}{space 4} -.056959{col 76}{space 3} .0538457
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0265917{col 35}{space 2} .0308522{col 46}{space 1}   -0.86{col 55}{space 3}0.390{col 63}{space 4}-.0873505{col 76}{space 3}  .034167
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0160298{col 35}{space 2} .0259802{col 46}{space 1}    0.62{col 55}{space 3}0.538{col 63}{space 4}-.0351342{col 76}{space 3} .0671938
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0166788{col 35}{space 2} .0222626{col 46}{space 1}   -0.75{col 55}{space 3}0.454{col 63}{space 4}-.0605216{col 76}{space 3} .0271641
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0089106{col 35}{space 2} .0220665{col 46}{space 1}   -0.40{col 55}{space 3}0.687{col 63}{space 4}-.0523673{col 76}{space 3}  .034546
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}-.0113499{col 35}{space 2}  .027323{col 46}{space 1}   -0.42{col 55}{space 3}0.678{col 63}{space 4}-.0651585{col 76}{space 3} .0424586
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0067146{col 35}{space 2} .0203005{col 46}{space 1}   -0.33{col 55}{space 3}0.741{col 63}{space 4}-.0466934{col 76}{space 3} .0332642
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} -.002544{col 35}{space 2} .0187357{col 46}{space 1}   -0.14{col 55}{space 3}0.892{col 63}{space 4} -.039441{col 76}{space 3} .0343531
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0161079{col 35}{space 2} .0159162{col 46}{space 1}    1.01{col 55}{space 3}0.312{col 63}{space 4}-.0152367{col 76}{space 3} .0474525
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} .0041649{col 35}{space 2} .0261567{col 46}{space 1}    0.16{col 55}{space 3}0.874{col 63}{space 4}-.0473468{col 76}{space 3} .0556766
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0105688{col 35}{space 2} .0288317{col 46}{space 1}   -0.37{col 55}{space 3}0.714{col 63}{space 4}-.0673484{col 76}{space 3} .0462109
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3764261{col 35}{space 2} .0390479{col 46}{space 1}    9.64{col 55}{space 3}0.000{col 63}{space 4} .2995271{col 76}{space 3}  .453325
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_partymbr
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if polparty==0, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    4160
                                                       {txt}F( 35,   519) ={res}   12.76
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0848
                                                       {txt}Root MSE      = {res} .48041

{txt}{ralign 87:(Std. Err. adjusted for {res:520} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0700998{col 35}{space 2} .0171123{col 46}{space 1}    4.10{col 55}{space 3}0.000{col 63}{space 4}  .036482{col 76}{space 3} .1037177
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0034916{col 35}{space 2}  .015251{col 46}{space 1}    0.23{col 55}{space 3}0.819{col 63}{space 4}-.0264697{col 76}{space 3} .0334529
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1294544{col 35}{space 2} .0194319{col 46}{space 1}   -6.66{col 55}{space 3}0.000{col 63}{space 4}-.1676292{col 76}{space 3}-.0912797
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1858774{col 35}{space 2} .0187215{col 46}{space 1}   -9.93{col 55}{space 3}0.000{col 63}{space 4}-.2226567{col 76}{space 3}-.1490982
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .1019024{col 35}{space 2} .0254763{col 46}{space 1}    4.00{col 55}{space 3}0.000{col 63}{space 4}  .051853{col 76}{space 3} .1519519
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0992287{col 35}{space 2} .0246345{col 46}{space 1}    4.03{col 55}{space 3}0.000{col 63}{space 4} .0508331{col 76}{space 3} .1476243
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1506266{col 35}{space 2} .0240476{col 46}{space 1}    6.26{col 55}{space 3}0.000{col 63}{space 4}  .103384{col 76}{space 3} .1978692
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2530125{col 35}{space 2} .0249019{col 46}{space 1}   10.16{col 55}{space 3}0.000{col 63}{space 4} .2040915{col 76}{space 3} .3019334
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2052119{col 35}{space 2}  .020398{col 46}{space 1}   10.06{col 55}{space 3}0.000{col 63}{space 4} .1651391{col 76}{space 3} .2452846
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0426388{col 35}{space 2} .0197348{col 46}{space 1}    2.16{col 55}{space 3}0.031{col 63}{space 4}  .003869{col 76}{space 3} .0814086
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0020746{col 35}{space 2} .0099405{col 46}{space 1}   -0.21{col 55}{space 3}0.835{col 63}{space 4}-.0216032{col 76}{space 3} .0174541
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0027515{col 35}{space 2} .0194832{col 46}{space 1}   -0.14{col 55}{space 3}0.888{col 63}{space 4} -.041027{col 76}{space 3}  .035524
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0123321{col 35}{space 2} .0120442{col 46}{space 1}   -1.02{col 55}{space 3}0.306{col 63}{space 4}-.0359936{col 76}{space 3} .0113293
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0271421{col 35}{space 2} .0151466{col 46}{space 1}    1.79{col 55}{space 3}0.074{col 63}{space 4}-.0026141{col 76}{space 3} .0568983
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0009864{col 35}{space 2} .0103025{col 46}{space 1}    0.10{col 55}{space 3}0.924{col 63}{space 4}-.0192533{col 76}{space 3} .0212261
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0065922{col 35}{space 2} .0183874{col 46}{space 1}   -0.36{col 55}{space 3}0.720{col 63}{space 4} -.042715{col 76}{space 3} .0295306
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0046619{col 35}{space 2} .0196901{col 46}{space 1}   -0.24{col 55}{space 3}0.813{col 63}{space 4}-.0433439{col 76}{space 3} .0340201
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0058804{col 35}{space 2}   .01997{col 46}{space 1}   -0.29{col 55}{space 3}0.769{col 63}{space 4}-.0451124{col 76}{space 3} .0333516
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0087723{col 35}{space 2} .0192502{col 46}{space 1}   -0.46{col 55}{space 3}0.649{col 63}{space 4}-.0465902{col 76}{space 3} .0290457
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0239582{col 35}{space 2} .0144259{col 46}{space 1}   -1.66{col 55}{space 3}0.097{col 63}{space 4}-.0522984{col 76}{space 3} .0043821
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0120904{col 35}{space 2} .0160779{col 46}{space 1}    0.75{col 55}{space 3}0.452{col 63}{space 4}-.0194953{col 76}{space 3} .0436761
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0149337{col 35}{space 2} .0136034{col 46}{space 1}   -1.10{col 55}{space 3}0.273{col 63}{space 4}-.0416582{col 76}{space 3} .0117907
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0069039{col 35}{space 2} .0142454{col 46}{space 1}    0.48{col 55}{space 3}0.628{col 63}{space 4}-.0210819{col 76}{space 3} .0348897
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0194027{col 35}{space 2} .0165743{col 46}{space 1}   -1.17{col 55}{space 3}0.242{col 63}{space 4}-.0519637{col 76}{space 3} .0131583
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0104939{col 35}{space 2} .0152653{col 46}{space 1}   -0.69{col 55}{space 3}0.492{col 63}{space 4}-.0404833{col 76}{space 3} .0194954
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0012568{col 35}{space 2}  .014329{col 46}{space 1}   -0.09{col 55}{space 3}0.930{col 63}{space 4}-.0294068{col 76}{space 3} .0268932
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0035958{col 35}{space 2} .0149039{col 46}{space 1}    0.24{col 55}{space 3}0.809{col 63}{space 4}-.0256835{col 76}{space 3}  .032875
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0013002{col 35}{space 2} .0160579{col 46}{space 1}    0.08{col 55}{space 3}0.935{col 63}{space 4}-.0302464{col 76}{space 3} .0328467
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0076892{col 35}{space 2} .0134228{col 46}{space 1}   -0.57{col 55}{space 3}0.567{col 63}{space 4}-.0340589{col 76}{space 3} .0186805
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0054182{col 35}{space 2} .0164414{col 46}{space 1}    0.33{col 55}{space 3}0.742{col 63}{space 4}-.0268817{col 76}{space 3} .0377182
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0064148{col 35}{space 2} .0151849{col 46}{space 1}   -0.42{col 55}{space 3}0.673{col 63}{space 4}-.0362461{col 76}{space 3} .0234165
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0049946{col 35}{space 2} .0163976{col 46}{space 1}    0.30{col 55}{space 3}0.761{col 63}{space 4}-.0272193{col 76}{space 3} .0372084
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0104558{col 35}{space 2} .0144524{col 46}{space 1}   -0.72{col 55}{space 3}0.470{col 63}{space 4}-.0388482{col 76}{space 3} .0179367
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0113212{col 35}{space 2} .0151792{col 46}{space 1}   -0.75{col 55}{space 3}0.456{col 63}{space 4}-.0411413{col 76}{space 3}  .018499
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0019864{col 35}{space 2} .0152356{col 46}{space 1}    0.13{col 55}{space 3}0.896{col 63}{space 4}-.0279447{col 76}{space 3} .0319175
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3766004{col 35}{space 2} .0294912{col 46}{space 1}   12.77{col 55}{space 3}0.000{col 63}{space 4} .3186635{col 76}{space 3} .4345372
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_noparty
{txt}
{com}.         
.         coefplot (chosen_partymbr, label(Belongs to Any Political Party) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_noparty, label(Not a Party Member) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_polparty.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_polparty.pdf written in PDF format)

{com}.                         
. 
. // FIGURE 8: Heterogeneity Results by Occupation.
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if boda==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2032
                                                       {txt}F( 35,   253) ={res}    7.61
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1034
                                                       {txt}Root MSE      = {res} .47771

{txt}{ralign 87:(Std. Err. adjusted for {res:254} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0975941{col 35}{space 2} .0254191{col 46}{space 1}    3.84{col 55}{space 3}0.000{col 63}{space 4}  .047534{col 76}{space 3} .1476541
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0322724{col 35}{space 2} .0224839{col 46}{space 1}    1.44{col 55}{space 3}0.152{col 63}{space 4} -.012007{col 76}{space 3} .0765518
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1640127{col 35}{space 2}  .028742{col 46}{space 1}   -5.71{col 55}{space 3}0.000{col 63}{space 4}-.2206169{col 76}{space 3}-.1074086
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2182131{col 35}{space 2} .0279494{col 46}{space 1}   -7.81{col 55}{space 3}0.000{col 63}{space 4}-.2732562{col 76}{space 3}-.1631699
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0692246{col 35}{space 2} .0347652{col 46}{space 1}    1.99{col 55}{space 3}0.048{col 63}{space 4} .0007585{col 76}{space 3} .1376906
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0937691{col 35}{space 2} .0353664{col 46}{space 1}    2.65{col 55}{space 3}0.009{col 63}{space 4}  .024119{col 76}{space 3} .1634192
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .103859{col 35}{space 2} .0345714{col 46}{space 1}    3.00{col 55}{space 3}0.003{col 63}{space 4} .0357746{col 76}{space 3} .1719435
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2492916{col 35}{space 2} .0345084{col 46}{space 1}    7.22{col 55}{space 3}0.000{col 63}{space 4} .1813314{col 76}{space 3} .3172519
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2190609{col 35}{space 2} .0294402{col 46}{space 1}    7.44{col 55}{space 3}0.000{col 63}{space 4} .1610819{col 76}{space 3} .2770399
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0614075{col 35}{space 2} .0282342{col 46}{space 1}    2.17{col 55}{space 3}0.031{col 63}{space 4} .0058034{col 76}{space 3} .1170116
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0139835{col 35}{space 2} .0243382{col 46}{space 1}   -0.57{col 55}{space 3}0.566{col 63}{space 4}-.0619147{col 76}{space 3} .0339478
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}  .018585{col 35}{space 2} .0229978{col 46}{space 1}    0.81{col 55}{space 3}0.420{col 63}{space 4}-.0267065{col 76}{space 3} .0638765
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0098501{col 35}{space 2} .0243104{col 46}{space 1}   -0.41{col 55}{space 3}0.686{col 63}{space 4}-.0577267{col 76}{space 3} .0380265
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0225214{col 35}{space 2} .0184895{col 46}{space 1}    1.22{col 55}{space 3}0.224{col 63}{space 4}-.0138916{col 76}{space 3} .0589344
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0061532{col 35}{space 2} .0189127{col 46}{space 1}    0.33{col 55}{space 3}0.745{col 63}{space 4}-.0310932{col 76}{space 3} .0433996
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2} .0115804{col 35}{space 2} .0247717{col 46}{space 1}    0.47{col 55}{space 3}0.641{col 63}{space 4}-.0372046{col 76}{space 3} .0603655
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0136494{col 35}{space 2} .0215312{col 46}{space 1}   -0.63{col 55}{space 3}0.527{col 63}{space 4}-.0560527{col 76}{space 3}  .028754
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2} .0053161{col 35}{space 2}  .019243{col 46}{space 1}    0.28{col 55}{space 3}0.783{col 63}{space 4}-.0325808{col 76}{space 3} .0432131
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2} .0115268{col 35}{space 2} .0285784{col 46}{space 1}    0.40{col 55}{space 3}0.687{col 63}{space 4}-.0447551{col 76}{space 3} .0678087
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2} -.042499{col 35}{space 2}  .022452{col 46}{space 1}   -1.89{col 55}{space 3}0.060{col 63}{space 4}-.0867155{col 76}{space 3} .0017176
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2}-.0033517{col 35}{space 2} .0193058{col 46}{space 1}   -0.17{col 55}{space 3}0.862{col 63}{space 4}-.0413722{col 76}{space 3} .0346687
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0250361{col 35}{space 2} .0278343{col 46}{space 1}   -0.90{col 55}{space 3}0.369{col 63}{space 4}-.0798526{col 76}{space 3} .0297804
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.0261279{col 35}{space 2} .0212497{col 46}{space 1}   -1.23{col 55}{space 3}0.220{col 63}{space 4}-.0679768{col 76}{space 3} .0157209
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0296247{col 35}{space 2} .0266962{col 46}{space 1}   -1.11{col 55}{space 3}0.268{col 63}{space 4}-.0821998{col 76}{space 3} .0229503
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0556816{col 35}{space 2} .0235048{col 46}{space 1}   -2.37{col 55}{space 3}0.019{col 63}{space 4}-.1019716{col 76}{space 3}-.0093916
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0079444{col 35}{space 2}  .029681{col 46}{space 1}   -0.27{col 55}{space 3}0.789{col 63}{space 4}-.0663976{col 76}{space 3} .0505089
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2}-.0172543{col 35}{space 2} .0221713{col 46}{space 1}   -0.78{col 55}{space 3}0.437{col 63}{space 4}-.0609181{col 76}{space 3} .0264096
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0331157{col 35}{space 2} .0235522{col 46}{space 1}   -1.41{col 55}{space 3}0.161{col 63}{space 4}-.0794992{col 76}{space 3} .0132677
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0133822{col 35}{space 2} .0258597{col 46}{space 1}   -0.52{col 55}{space 3}0.605{col 63}{space 4}  -.06431{col 76}{space 3} .0375456
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}-.0290928{col 35}{space 2} .0328591{col 46}{space 1}   -0.89{col 55}{space 3}0.377{col 63}{space 4}-.0938049{col 76}{space 3} .0356193
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}  .001184{col 35}{space 2} .0231043{col 46}{space 1}    0.05{col 55}{space 3}0.959{col 63}{space 4}-.0443173{col 76}{space 3} .0466854
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0208447{col 35}{space 2} .0223995{col 46}{space 1}   -0.93{col 55}{space 3}0.353{col 63}{space 4}-.0649579{col 76}{space 3} .0232686
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0125948{col 35}{space 2} .0232058{col 46}{space 1}   -0.54{col 55}{space 3}0.588{col 63}{space 4}-.0582959{col 76}{space 3} .0331063
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} -.014638{col 35}{space 2} .0225395{col 46}{space 1}   -0.65{col 55}{space 3}0.517{col 63}{space 4} -.059027{col 76}{space 3}  .029751
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0163086{col 35}{space 2}  .022387{col 46}{space 1}   -0.73{col 55}{space 3}0.467{col 63}{space 4}-.0603972{col 76}{space 3}   .02778
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2}  .384379{col 35}{space 2} .0391872{col 46}{space 1}    9.81{col 55}{space 3}0.000{col 63}{space 4} .3072045{col 76}{space 3} .4615536
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_boda
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if market==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2056
                                                       {txt}F( 35,   256) ={res}    7.80
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0921
                                                       {txt}Root MSE      = {res} .48064

{txt}{ralign 87:(Std. Err. adjusted for {res:257} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0869576{col 35}{space 2} .0237426{col 46}{space 1}    3.66{col 55}{space 3}0.000{col 63}{space 4} .0402019{col 76}{space 3} .1337132
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2}-.0117939{col 35}{space 2}  .022296{col 46}{space 1}   -0.53{col 55}{space 3}0.597{col 63}{space 4}-.0557008{col 76}{space 3} .0321129
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1677477{col 35}{space 2} .0259954{col 46}{space 1}   -6.45{col 55}{space 3}0.000{col 63}{space 4}-.2189398{col 76}{space 3}-.1165556
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1825987{col 35}{space 2} .0259635{col 46}{space 1}   -7.03{col 55}{space 3}0.000{col 63}{space 4}-.2337279{col 76}{space 3}-.1314695
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .1051004{col 35}{space 2}  .035235{col 46}{space 1}    2.98{col 55}{space 3}0.003{col 63}{space 4}  .035713{col 76}{space 3} .1744878
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .1058402{col 35}{space 2} .0355447{col 46}{space 1}    2.98{col 55}{space 3}0.003{col 63}{space 4} .0358428{col 76}{space 3} .1758375
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1549594{col 35}{space 2} .0342176{col 46}{space 1}    4.53{col 55}{space 3}0.000{col 63}{space 4} .0875756{col 76}{space 3} .2223433
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2470623{col 35}{space 2} .0358473{col 46}{space 1}    6.89{col 55}{space 3}0.000{col 63}{space 4} .1764691{col 76}{space 3} .3176555
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2009048{col 35}{space 2} .0294283{col 46}{space 1}    6.83{col 55}{space 3}0.000{col 63}{space 4} .1429525{col 76}{space 3} .2588571
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0080237{col 35}{space 2} .0285828{col 46}{space 1}    0.28{col 55}{space 3}0.779{col 63}{space 4}-.0482637{col 76}{space 3} .0643112
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0147205{col 35}{space 2}  .024805{col 46}{space 1}   -0.59{col 55}{space 3}0.553{col 63}{space 4}-.0635683{col 76}{space 3} .0341273
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0485546{col 35}{space 2} .0389341{col 46}{space 1}   -1.25{col 55}{space 3}0.214{col 63}{space 4}-.1252266{col 76}{space 3} .0281174
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2} .0011556{col 35}{space 2} .0257644{col 46}{space 1}    0.04{col 55}{space 3}0.964{col 63}{space 4}-.0495816{col 76}{space 3} .0518928
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}  .008938{col 35}{space 2} .0221975{col 46}{space 1}    0.40{col 55}{space 3}0.688{col 63}{space 4} -.034775{col 76}{space 3}  .052651
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0211964{col 35}{space 2} .0198778{col 46}{space 1}    1.07{col 55}{space 3}0.287{col 63}{space 4}-.0179483{col 76}{space 3} .0603412
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0280449{col 35}{space 2} .0329908{col 46}{space 1}   -0.85{col 55}{space 3}0.396{col 63}{space 4}-.0930128{col 76}{space 3}  .036923
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0506542{col 35}{space 2} .0412775{col 46}{space 1}   -1.23{col 55}{space 3}0.221{col 63}{space 4}-.1319409{col 76}{space 3} .0306325
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0403274{col 35}{space 2}  .036862{col 46}{space 1}   -1.09{col 55}{space 3}0.275{col 63}{space 4}-.1129186{col 76}{space 3} .0322639
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0625315{col 35}{space 2} .0410569{col 46}{space 1}   -1.52{col 55}{space 3}0.129{col 63}{space 4}-.1433837{col 76}{space 3} .0183207
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0116054{col 35}{space 2} .0221526{col 46}{space 1}   -0.52{col 55}{space 3}0.601{col 63}{space 4}  -.05523{col 76}{space 3} .0320192
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} -.013029{col 35}{space 2} .0226649{col 46}{space 1}   -0.57{col 55}{space 3}0.566{col 63}{space 4}-.0576624{col 76}{space 3} .0316043
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0352519{col 35}{space 2} .0271665{col 46}{space 1}   -1.30{col 55}{space 3}0.196{col 63}{space 4}-.0887502{col 76}{space 3} .0182464
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0263559{col 35}{space 2} .0326966{col 46}{space 1}    0.81{col 55}{space 3}0.421{col 63}{space 4}-.0380327{col 76}{space 3} .0907445
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0379008{col 35}{space 2} .0309141{col 46}{space 1}   -1.23{col 55}{space 3}0.221{col 63}{space 4}-.0987791{col 76}{space 3} .0229775
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} .0410056{col 35}{space 2} .0316836{col 46}{space 1}    1.29{col 55}{space 3}0.197{col 63}{space 4}-.0213881{col 76}{space 3} .1033993
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2} .0168263{col 35}{space 2} .0300577{col 46}{space 1}    0.56{col 55}{space 3}0.576{col 63}{space 4}-.0423656{col 76}{space 3} .0760181
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0786697{col 35}{space 2}  .031298{col 46}{space 1}    2.51{col 55}{space 3}0.013{col 63}{space 4} .0170353{col 76}{space 3} .1403041
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0403125{col 35}{space 2} .0284287{col 46}{space 1}    1.42{col 55}{space 3}0.157{col 63}{space 4}-.0156713{col 76}{space 3} .0962963
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0251561{col 35}{space 2} .0282787{col 46}{space 1}   -0.89{col 55}{space 3}0.375{col 63}{space 4}-.0808445{col 76}{space 3} .0305323
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0475433{col 35}{space 2}  .029829{col 46}{space 1}    1.59{col 55}{space 3}0.112{col 63}{space 4}-.0111982{col 76}{space 3} .1062847
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0510794{col 35}{space 2} .0304894{col 46}{space 1}   -1.68{col 55}{space 3}0.095{col 63}{space 4}-.1111215{col 76}{space 3} .0089627
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0031146{col 35}{space 2} .0318066{col 46}{space 1}   -0.10{col 55}{space 3}0.922{col 63}{space 4}-.0657504{col 76}{space 3} .0595212
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0147754{col 35}{space 2} .0288243{col 46}{space 1}   -0.51{col 55}{space 3}0.609{col 63}{space 4}-.0715383{col 76}{space 3} .0419876
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} .0027983{col 35}{space 2} .0235053{col 46}{space 1}    0.12{col 55}{space 3}0.905{col 63}{space 4}-.0434901{col 76}{space 3} .0490866
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0242121{col 35}{space 2} .0216146{col 46}{space 1}    1.12{col 55}{space 3}0.264{col 63}{space 4}-.0183529{col 76}{space 3} .0667771
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .4060334{col 35}{space 2}  .046878{col 46}{space 1}    8.66{col 55}{space 3}0.000{col 63}{space 4} .3137178{col 76}{space 3} .4983489
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_mkt
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if shop==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2136
                                                       {txt}F( 35,   266) ={res}    8.80
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0994
                                                       {txt}Root MSE      = {res} .47855

{txt}{ralign 87:(Std. Err. adjusted for {res:267} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1136705{col 35}{space 2} .0236437{col 46}{space 1}    4.81{col 55}{space 3}0.000{col 63}{space 4} .0671179{col 76}{space 3}  .160223
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0252031{col 35}{space 2} .0209112{col 46}{space 1}    1.21{col 55}{space 3}0.229{col 63}{space 4}-.0159694{col 76}{space 3} .0663756
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2} -.105971{col 35}{space 2} .0278499{col 46}{space 1}   -3.81{col 55}{space 3}0.000{col 63}{space 4}-.1608053{col 76}{space 3}-.0511367
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1912951{col 35}{space 2} .0276728{col 46}{space 1}   -6.91{col 55}{space 3}0.000{col 63}{space 4}-.2457807{col 76}{space 3}-.1368096
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0805408{col 35}{space 2} .0385344{col 46}{space 1}    2.09{col 55}{space 3}0.038{col 63}{space 4} .0046695{col 76}{space 3} .1564121
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0694671{col 35}{space 2} .0349021{col 46}{space 1}    1.99{col 55}{space 3}0.048{col 63}{space 4} .0007476{col 76}{space 3} .1381866
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1438999{col 35}{space 2}  .035601{col 46}{space 1}    4.04{col 55}{space 3}0.000{col 63}{space 4} .0738044{col 76}{space 3} .2139955
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2490096{col 35}{space 2} .0364139{col 46}{space 1}    6.84{col 55}{space 3}0.000{col 63}{space 4} .1773134{col 76}{space 3} .3207058
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2}  .210576{col 35}{space 2}  .026723{col 46}{space 1}    7.88{col 55}{space 3}0.000{col 63}{space 4} .1579605{col 76}{space 3} .2631915
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0246557{col 35}{space 2} .0271956{col 46}{space 1}    0.91{col 55}{space 3}0.365{col 63}{space 4}-.0288903{col 76}{space 3} .0782017
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}  .010296{col 35}{space 2} .0281567{col 46}{space 1}    0.37{col 55}{space 3}0.715{col 63}{space 4}-.0451424{col 76}{space 3} .0657345
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0318079{col 35}{space 2} .0341931{col 46}{space 1}   -0.93{col 55}{space 3}0.353{col 63}{space 4}-.0991315{col 76}{space 3} .0355156
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0490168{col 35}{space 2} .0248515{col 46}{space 1}   -1.97{col 55}{space 3}0.050{col 63}{space 4}-.0979475{col 76}{space 3}-.0000862
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0247811{col 35}{space 2} .0190479{col 46}{space 1}   -1.30{col 55}{space 3}0.194{col 63}{space 4}-.0622849{col 76}{space 3} .0127227
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0203519{col 35}{space 2} .0206435{col 46}{space 1}   -0.99{col 55}{space 3}0.325{col 63}{space 4}-.0609975{col 76}{space 3} .0202936
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0304866{col 35}{space 2} .0395808{col 46}{space 1}   -0.77{col 55}{space 3}0.442{col 63}{space 4}-.1084182{col 76}{space 3} .0474449
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}  -.00318{col 35}{space 2} .0374818{col 46}{space 1}   -0.08{col 55}{space 3}0.932{col 63}{space 4}-.0769787{col 76}{space 3} .0706187
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0334757{col 35}{space 2} .0352213{col 46}{space 1}   -0.95{col 55}{space 3}0.343{col 63}{space 4}-.1028237{col 76}{space 3} .0358723
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0297601{col 35}{space 2} .0336893{col 46}{space 1}   -0.88{col 55}{space 3}0.378{col 63}{space 4}-.0960917{col 76}{space 3} .0365714
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0088219{col 35}{space 2} .0183087{col 46}{space 1}   -0.48{col 55}{space 3}0.630{col 63}{space 4}-.0448704{col 76}{space 3} .0272266
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0262539{col 35}{space 2} .0221328{col 46}{space 1}    1.19{col 55}{space 3}0.237{col 63}{space 4}-.0173238{col 76}{space 3} .0698316
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0248557{col 35}{space 2} .0252044{col 46}{space 1}   -0.99{col 55}{space 3}0.325{col 63}{space 4}-.0744813{col 76}{space 3} .0247698
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0256098{col 35}{space 2} .0298198{col 46}{space 1}    0.86{col 55}{space 3}0.391{col 63}{space 4}-.0331031{col 76}{space 3} .0843228
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0366008{col 35}{space 2} .0346035{col 46}{space 1}   -1.06{col 55}{space 3}0.291{col 63}{space 4}-.1047324{col 76}{space 3} .0315307
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0129312{col 35}{space 2} .0281666{col 46}{space 1}   -0.46{col 55}{space 3}0.647{col 63}{space 4}-.0683891{col 76}{space 3} .0425267
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0104426{col 35}{space 2} .0283968{col 46}{space 1}   -0.37{col 55}{space 3}0.713{col 63}{space 4}-.0663537{col 76}{space 3} .0454686
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} -.019633{col 35}{space 2} .0272201{col 46}{space 1}   -0.72{col 55}{space 3}0.471{col 63}{space 4}-.0732272{col 76}{space 3} .0339613
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0128747{col 35}{space 2} .0282572{col 46}{space 1}   -0.46{col 55}{space 3}0.649{col 63}{space 4}-.0685108{col 76}{space 3} .0427615
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0349594{col 35}{space 2} .0277251{col 46}{space 1}   -1.26{col 55}{space 3}0.208{col 63}{space 4}-.0895479{col 76}{space 3} .0196291
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0134324{col 35}{space 2} .0323389{col 46}{space 1}    0.42{col 55}{space 3}0.678{col 63}{space 4}-.0502405{col 76}{space 3} .0771052
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0160764{col 35}{space 2}  .027526{col 46}{space 1}   -0.58{col 55}{space 3}0.560{col 63}{space 4}-.0702731{col 76}{space 3} .0381202
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0336294{col 35}{space 2} .0321519{col 46}{space 1}   -1.05{col 55}{space 3}0.297{col 63}{space 4} -.096934{col 76}{space 3} .0296752
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0188958{col 35}{space 2} .0286524{col 46}{space 1}   -0.66{col 55}{space 3}0.510{col 63}{space 4}-.0753101{col 76}{space 3} .0375185
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0020459{col 35}{space 2} .0225784{col 46}{space 1}   -0.09{col 55}{space 3}0.928{col 63}{space 4}-.0465011{col 76}{space 3} .0424092
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0083741{col 35}{space 2} .0249854{col 46}{space 1}    0.34{col 55}{space 3}0.738{col 63}{space 4}-.0408203{col 76}{space 3} .0575685
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3737934{col 35}{space 2} .0446897{col 46}{space 1}    8.36{col 55}{space 3}0.000{col 63}{space 4} .2858027{col 76}{space 3}  .461784
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_shop      
{txt}
{com}.         
.         coefplot (chosen_boda, label(Motorcycle Taxi) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_shop, label(Shopkeepers) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)) ///
>                 (chosen_mkt, label(Market vendors) msymbol(triangle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(8) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_occ.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_occ.pdf written in PDF format)

{com}.  
.  
. // FIGURE 9: Heterogeneity results by whether respondent is of age 30 or higher. 
. 
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if age<=30 & age!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    3032
                                                       {txt}F( 35,   378) ={res}   13.41
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1069
                                                       {txt}Root MSE      = {res} .47536

{txt}{ralign 87:(Std. Err. adjusted for {res:379} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1057666{col 35}{space 2} .0206168{col 46}{space 1}    5.13{col 55}{space 3}0.000{col 63}{space 4} .0652285{col 76}{space 3} .1463046
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0282486{col 35}{space 2}  .018152{col 46}{space 1}    1.56{col 55}{space 3}0.120{col 63}{space 4}-.0074429{col 76}{space 3} .0639402
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2} -.154059{col 35}{space 2} .0225975{col 46}{space 1}   -6.82{col 55}{space 3}0.000{col 63}{space 4}-.1984916{col 76}{space 3}-.1096265
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2012946{col 35}{space 2} .0225521{col 46}{space 1}   -8.93{col 55}{space 3}0.000{col 63}{space 4}-.2456379{col 76}{space 3}-.1569512
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0540382{col 35}{space 2} .0301037{col 46}{space 1}    1.80{col 55}{space 3}0.073{col 63}{space 4}-.0051534{col 76}{space 3} .1132299
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0704413{col 35}{space 2} .0298139{col 46}{space 1}    2.36{col 55}{space 3}0.019{col 63}{space 4} .0118195{col 76}{space 3} .1290631
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1146455{col 35}{space 2} .0291337{col 46}{space 1}    3.94{col 55}{space 3}0.000{col 63}{space 4} .0573611{col 76}{space 3} .1719299
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2353567{col 35}{space 2} .0287968{col 46}{space 1}    8.17{col 55}{space 3}0.000{col 63}{space 4} .1787348{col 76}{space 3} .2919786
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2358018{col 35}{space 2} .0230773{col 46}{space 1}   10.22{col 55}{space 3}0.000{col 63}{space 4} .1904257{col 76}{space 3} .2811778
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0384862{col 35}{space 2}  .023434{col 46}{space 1}    1.64{col 55}{space 3}0.101{col 63}{space 4}-.0075912{col 76}{space 3} .0845636
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0144268{col 35}{space 2} .0138419{col 46}{space 1}   -1.04{col 55}{space 3}0.298{col 63}{space 4}-.0416435{col 76}{space 3} .0127899
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}  .018723{col 35}{space 2} .0232771{col 46}{space 1}    0.80{col 55}{space 3}0.422{col 63}{space 4}-.0270458{col 76}{space 3} .0644919
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0211129{col 35}{space 2} .0140981{col 46}{space 1}   -1.50{col 55}{space 3}0.135{col 63}{space 4}-.0488334{col 76}{space 3} .0066075
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0108216{col 35}{space 2}  .015257{col 46}{space 1}    0.71{col 55}{space 3}0.479{col 63}{space 4}-.0191776{col 76}{space 3} .0408209
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} -.002313{col 35}{space 2} .0132376{col 46}{space 1}   -0.17{col 55}{space 3}0.861{col 63}{space 4}-.0283416{col 76}{space 3} .0237156
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2} .0069001{col 35}{space 2} .0231737{col 46}{space 1}    0.30{col 55}{space 3}0.766{col 63}{space 4}-.0386655{col 76}{space 3} .0524656
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2} .0155563{col 35}{space 2} .0228465{col 46}{space 1}    0.68{col 55}{space 3}0.496{col 63}{space 4}-.0293658{col 76}{space 3} .0604784
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2} .0055392{col 35}{space 2} .0234651{col 46}{space 1}    0.24{col 55}{space 3}0.814{col 63}{space 4}-.0405994{col 76}{space 3} .0516777
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2} .0219991{col 35}{space 2} .0231365{col 46}{space 1}    0.95{col 55}{space 3}0.342{col 63}{space 4}-.0234932{col 76}{space 3} .0674914
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0124037{col 35}{space 2} .0206411{col 46}{space 1}   -0.60{col 55}{space 3}0.548{col 63}{space 4}-.0529895{col 76}{space 3} .0281821
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0211016{col 35}{space 2} .0197495{col 46}{space 1}    1.07{col 55}{space 3}0.286{col 63}{space 4}-.0177309{col 76}{space 3} .0599342
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2} -.011636{col 35}{space 2} .0168698{col 46}{space 1}   -0.69{col 55}{space 3}0.491{col 63}{space 4}-.0448065{col 76}{space 3} .0215344
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.0092446{col 35}{space 2} .0180778{col 46}{space 1}   -0.51{col 55}{space 3}0.609{col 63}{space 4}-.0447903{col 76}{space 3} .0263011
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2} .0121897{col 35}{space 2} .0208365{col 46}{space 1}    0.59{col 55}{space 3}0.559{col 63}{space 4}-.0287803{col 76}{space 3} .0531598
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0177241{col 35}{space 2} .0211672{col 46}{space 1}   -0.84{col 55}{space 3}0.403{col 63}{space 4}-.0593444{col 76}{space 3} .0238961
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0055713{col 35}{space 2} .0194438{col 46}{space 1}   -0.29{col 55}{space 3}0.775{col 63}{space 4}-.0438029{col 76}{space 3} .0326604
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0125052{col 35}{space 2} .0177242{col 46}{space 1}    0.71{col 55}{space 3}0.481{col 63}{space 4}-.0223452{col 76}{space 3} .0473555
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0152184{col 35}{space 2} .0222501{col 46}{space 1}   -0.68{col 55}{space 3}0.494{col 63}{space 4}-.0589678{col 76}{space 3}  .028531
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}  .017312{col 35}{space 2} .0188421{col 46}{space 1}    0.92{col 55}{space 3}0.359{col 63}{space 4}-.0197365{col 76}{space 3} .0543605
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0008912{col 35}{space 2} .0210482{col 46}{space 1}    0.04{col 55}{space 3}0.966{col 63}{space 4} -.040495{col 76}{space 3} .0422775
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}  .013239{col 35}{space 2} .0200738{col 46}{space 1}    0.66{col 55}{space 3}0.510{col 63}{space 4}-.0262314{col 76}{space 3} .0527094
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0095779{col 35}{space 2} .0180512{col 46}{space 1}    0.53{col 55}{space 3}0.596{col 63}{space 4}-.0259153{col 76}{space 3} .0450712
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0086971{col 35}{space 2} .0179877{col 46}{space 1}    0.48{col 55}{space 3}0.629{col 63}{space 4}-.0266714{col 76}{space 3} .0440656
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0076037{col 35}{space 2} .0214361{col 46}{space 1}   -0.35{col 55}{space 3}0.723{col 63}{space 4}-.0497526{col 76}{space 3} .0345452
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}  .008098{col 35}{space 2}  .020832{col 46}{space 1}    0.39{col 55}{space 3}0.698{col 63}{space 4}-.0328632{col 76}{space 3} .0490592
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2}   .36111{col 35}{space 2} .0361272{col 46}{space 1}   10.00{col 55}{space 3}0.000{col 63}{space 4} .2900745{col 76}{space 3} .4321455
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_young
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if age>30 & age!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    3184
                                                       {txt}F( 35,   397) ={res}   10.02
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0874
                                                       {txt}Root MSE      = {res} .48037

{txt}{ralign 87:(Std. Err. adjusted for {res:398} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0935668{col 35}{space 2} .0186515{col 46}{space 1}    5.02{col 55}{space 3}0.000{col 63}{space 4} .0568989{col 76}{space 3} .1302348
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0028211{col 35}{space 2} .0175542{col 46}{space 1}    0.16{col 55}{space 3}0.872{col 63}{space 4}-.0316898{col 76}{space 3}  .037332
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1359413{col 35}{space 2} .0222616{col 46}{space 1}   -6.11{col 55}{space 3}0.000{col 63}{space 4}-.1797066{col 76}{space 3}-.0921759
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1928666{col 35}{space 2} .0215519{col 46}{space 1}   -8.95{col 55}{space 3}0.000{col 63}{space 4}-.2352367{col 76}{space 3}-.1504965
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .1146578{col 35}{space 2} .0289411{col 46}{space 1}    3.96{col 55}{space 3}0.000{col 63}{space 4} .0577609{col 76}{space 3} .1715547
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .1061984{col 35}{space 2} .0275267{col 46}{space 1}    3.86{col 55}{space 3}0.000{col 63}{space 4} .0520821{col 76}{space 3} .1603148
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1537636{col 35}{space 2} .0275568{col 46}{space 1}    5.58{col 55}{space 3}0.000{col 63}{space 4} .0995882{col 76}{space 3} .2079391
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2625485{col 35}{space 2} .0290614{col 46}{space 1}    9.03{col 55}{space 3}0.000{col 63}{space 4} .2054151{col 76}{space 3} .3196819
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .1789027{col 35}{space 2} .0232347{col 46}{space 1}    7.70{col 55}{space 3}0.000{col 63}{space 4} .1332243{col 76}{space 3}  .224581
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0230354{col 35}{space 2} .0223563{col 46}{space 1}    1.03{col 55}{space 3}0.303{col 63}{space 4}-.0209161{col 76}{space 3}  .066987
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0053404{col 35}{space 2} .0104369{col 46}{space 1}   -0.51{col 55}{space 3}0.609{col 63}{space 4}-.0258588{col 76}{space 3} .0151781
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0304757{col 35}{space 2}  .019476{col 46}{space 1}   -1.56{col 55}{space 3}0.118{col 63}{space 4}-.0687646{col 76}{space 3} .0078132
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0186409{col 35}{space 2} .0103637{col 46}{space 1}   -1.80{col 55}{space 3}0.073{col 63}{space 4}-.0390154{col 76}{space 3} .0017336
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0057722{col 35}{space 2} .0131228{col 46}{space 1}   -0.44{col 55}{space 3}0.660{col 63}{space 4} -.031571{col 76}{space 3} .0200265
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0053397{col 35}{space 2} .0109902{col 46}{space 1}    0.49{col 55}{space 3}0.627{col 63}{space 4}-.0162666{col 76}{space 3} .0269459
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0307636{col 35}{space 2} .0180672{col 46}{space 1}   -1.70{col 55}{space 3}0.089{col 63}{space 4} -.066283{col 76}{space 3} .0047558
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0450872{col 35}{space 2} .0192205{col 46}{space 1}   -2.35{col 55}{space 3}0.019{col 63}{space 4}-.0828738{col 76}{space 3}-.0073005
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2} -.034057{col 35}{space 2} .0192028{col 46}{space 1}   -1.77{col 55}{space 3}0.077{col 63}{space 4}-.0718088{col 76}{space 3} .0036949
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0295103{col 35}{space 2} .0195019{col 46}{space 1}   -1.51{col 55}{space 3}0.131{col 63}{space 4}-.0678502{col 76}{space 3} .0088297
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0236124{col 35}{space 2} .0139704{col 46}{space 1}   -1.69{col 55}{space 3}0.092{col 63}{space 4}-.0510777{col 76}{space 3} .0038529
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2}-.0038266{col 35}{space 2} .0149216{col 46}{space 1}   -0.26{col 55}{space 3}0.798{col 63}{space 4}-.0331618{col 76}{space 3} .0255086
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0205837{col 35}{space 2} .0150441{col 46}{space 1}   -1.37{col 55}{space 3}0.172{col 63}{space 4}-.0501598{col 76}{space 3} .0089923
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0283935{col 35}{space 2} .0161049{col 46}{space 1}    1.76{col 55}{space 3}0.079{col 63}{space 4}-.0032681{col 76}{space 3}  .060055
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0503034{col 35}{space 2} .0219863{col 46}{space 1}   -2.29{col 55}{space 3}0.023{col 63}{space 4}-.0935275{col 76}{space 3}-.0070793
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} .0037247{col 35}{space 2}  .014826{col 46}{space 1}    0.25{col 55}{space 3}0.802{col 63}{space 4}-.0254226{col 76}{space 3} .0328719
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0051558{col 35}{space 2}  .015761{col 46}{space 1}   -0.33{col 55}{space 3}0.744{col 63}{space 4}-.0361412{col 76}{space 3} .0258296
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0098101{col 35}{space 2} .0174426{col 46}{space 1}    0.56{col 55}{space 3}0.574{col 63}{space 4}-.0244814{col 76}{space 3} .0441016
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0148769{col 35}{space 2} .0155344{col 46}{space 1}    0.96{col 55}{space 3}0.339{col 63}{space 4} -.015663{col 76}{space 3} .0454169
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0306819{col 35}{space 2} .0141073{col 46}{space 1}   -2.17{col 55}{space 3}0.030{col 63}{space 4}-.0584162{col 76}{space 3}-.0029476
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}  .017465{col 35}{space 2} .0188246{col 46}{space 1}    0.93{col 55}{space 3}0.354{col 63}{space 4}-.0195433{col 76}{space 3} .0544733
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0244306{col 35}{space 2} .0152701{col 46}{space 1}   -1.60{col 55}{space 3}0.110{col 63}{space 4} -.054451{col 76}{space 3} .0055897
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0078142{col 35}{space 2} .0157199{col 46}{space 1}   -0.50{col 55}{space 3}0.619{col 63}{space 4}-.0387189{col 76}{space 3} .0230906
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} -.010925{col 35}{space 2} .0145059{col 46}{space 1}   -0.75{col 55}{space 3}0.452{col 63}{space 4}-.0394429{col 76}{space 3}  .017593
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0024436{col 35}{space 2}  .015376{col 46}{space 1}   -0.16{col 55}{space 3}0.874{col 63}{space 4}-.0326722{col 76}{space 3} .0277849
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0061178{col 35}{space 2} .0155317{col 46}{space 1}    0.39{col 55}{space 3}0.694{col 63}{space 4} -.024417{col 76}{space 3} .0366525
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3939325{col 35}{space 2} .0301173{col 46}{space 1}   13.08{col 55}{space 3}0.000{col 63}{space 4} .3347231{col 76}{space 3} .4531419
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_old       
{txt}
{com}.         
.         coefplot (chosen_young, label(Age<30) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_old, label(Age>30) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_age.pdf", as(pdf) replace      
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_age.pdf written in PDF format)

{com}.                 
.                 
. // FIGURE 10: Heterogeneity Results by Gender. 
. 
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if male==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    3560
                                                       {txt}F( 35,   444) ={res}   12.32
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0995
                                                       {txt}Root MSE      = {res} .47689

{txt}{ralign 87:(Std. Err. adjusted for {res:445} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2}  .092502{col 35}{space 2} .0180076{col 46}{space 1}    5.14{col 55}{space 3}0.000{col 63}{space 4} .0571113{col 76}{space 3} .1278927
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0047403{col 35}{space 2} .0171563{col 46}{space 1}    0.28{col 55}{space 3}0.782{col 63}{space 4}-.0289773{col 76}{space 3} .0384578
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1573433{col 35}{space 2}  .021356{col 46}{space 1}   -7.37{col 55}{space 3}0.000{col 63}{space 4}-.1993146{col 76}{space 3} -.115372
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2031509{col 35}{space 2} .0210186{col 46}{space 1}   -9.67{col 55}{space 3}0.000{col 63}{space 4}-.2444592{col 76}{space 3}-.1618427
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0839202{col 35}{space 2} .0275637{col 46}{space 1}    3.04{col 55}{space 3}0.002{col 63}{space 4} .0297487{col 76}{space 3} .1380917
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0994073{col 35}{space 2} .0271163{col 46}{space 1}    3.67{col 55}{space 3}0.000{col 63}{space 4}  .046115{col 76}{space 3} .1526996
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1133879{col 35}{space 2} .0269409{col 46}{space 1}    4.21{col 55}{space 3}0.000{col 63}{space 4} .0604403{col 76}{space 3} .1663354
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2752324{col 35}{space 2} .0271694{col 46}{space 1}   10.13{col 55}{space 3}0.000{col 63}{space 4} .2218359{col 76}{space 3} .3286289
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .1962271{col 35}{space 2} .0218783{col 46}{space 1}    8.97{col 55}{space 3}0.000{col 63}{space 4} .1532291{col 76}{space 3}  .239225
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0338599{col 35}{space 2} .0214484{col 46}{space 1}    1.58{col 55}{space 3}0.115{col 63}{space 4}-.0082932{col 76}{space 3}  .076013
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0143957{col 35}{space 2} .0107537{col 46}{space 1}   -1.34{col 55}{space 3}0.181{col 63}{space 4}-.0355303{col 76}{space 3} .0067388
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2} .0094516{col 35}{space 2}   .01955{col 46}{space 1}    0.48{col 55}{space 3}0.629{col 63}{space 4}-.0289705{col 76}{space 3} .0478737
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2} -.022575{col 35}{space 2} .0112956{col 46}{space 1}   -2.00{col 55}{space 3}0.046{col 63}{space 4}-.0447745{col 76}{space 3}-.0003754
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0131764{col 35}{space 2} .0123245{col 46}{space 1}    1.07{col 55}{space 3}0.286{col 63}{space 4}-.0110451{col 76}{space 3}  .037398
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0074154{col 35}{space 2} .0108479{col 46}{space 1}    0.68{col 55}{space 3}0.495{col 63}{space 4}-.0139042{col 76}{space 3}  .028735
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0042335{col 35}{space 2} .0199985{col 46}{space 1}   -0.21{col 55}{space 3}0.832{col 63}{space 4}-.0435371{col 76}{space 3} .0350701
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2} .0058179{col 35}{space 2} .0188166{col 46}{space 1}    0.31{col 55}{space 3}0.757{col 63}{space 4}-.0311628{col 76}{space 3} .0427985
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0006624{col 35}{space 2} .0189965{col 46}{space 1}   -0.03{col 55}{space 3}0.972{col 63}{space 4}-.0379966{col 76}{space 3} .0366718
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2} .0055774{col 35}{space 2} .0195432{col 46}{space 1}    0.29{col 55}{space 3}0.775{col 63}{space 4}-.0328312{col 76}{space 3}  .043986
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0224649{col 35}{space 2} .0152651{col 46}{space 1}   -1.47{col 55}{space 3}0.142{col 63}{space 4}-.0524659{col 76}{space 3}  .007536
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0066022{col 35}{space 2} .0145746{col 46}{space 1}    0.45{col 55}{space 3}0.651{col 63}{space 4}-.0220415{col 76}{space 3} .0352459
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0102563{col 35}{space 2} .0133245{col 46}{space 1}   -0.77{col 55}{space 3}0.442{col 63}{space 4}-.0364432{col 76}{space 3} .0159305
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.0152848{col 35}{space 2} .0176417{col 46}{space 1}   -0.87{col 55}{space 3}0.387{col 63}{space 4}-.0499565{col 76}{space 3} .0193869
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0124253{col 35}{space 2} .0167059{col 46}{space 1}   -0.74{col 55}{space 3}0.457{col 63}{space 4}-.0452579{col 76}{space 3} .0204072
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0163729{col 35}{space 2} .0196401{col 46}{space 1}   -0.83{col 55}{space 3}0.405{col 63}{space 4} -.054972{col 76}{space 3} .0222262
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2} .0078639{col 35}{space 2} .0190451{col 46}{space 1}    0.41{col 55}{space 3}0.680{col 63}{space 4}-.0295658{col 76}{space 3} .0452936
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0032075{col 35}{space 2} .0177422{col 46}{space 1}    0.18{col 55}{space 3}0.857{col 63}{space 4}-.0316617{col 76}{space 3} .0380767
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0134833{col 35}{space 2} .0196745{col 46}{space 1}   -0.69{col 55}{space 3}0.493{col 63}{space 4}-.0521501{col 76}{space 3} .0251834
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2} .0015556{col 35}{space 2} .0143016{col 46}{space 1}    0.11{col 55}{space 3}0.913{col 63}{space 4}-.0265516{col 76}{space 3} .0296628
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} -.010746{col 35}{space 2} .0198976{col 46}{space 1}   -0.54{col 55}{space 3}0.589{col 63}{space 4}-.0498512{col 76}{space 3} .0283592
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}  .011073{col 35}{space 2} .0124065{col 46}{space 1}    0.89{col 55}{space 3}0.373{col 63}{space 4}-.0133098{col 76}{space 3} .0354557
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0010478{col 35}{space 2} .0146626{col 46}{space 1}    0.07{col 55}{space 3}0.943{col 63}{space 4} -.027769{col 76}{space 3} .0298646
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0039397{col 35}{space 2} .0129162{col 46}{space 1}   -0.31{col 55}{space 3}0.760{col 63}{space 4}-.0293242{col 76}{space 3} .0214449
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0197847{col 35}{space 2} .0183022{col 46}{space 1}   -1.08{col 55}{space 3}0.280{col 63}{space 4}-.0557543{col 76}{space 3}  .016185
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0122882{col 35}{space 2} .0188967{col 46}{space 1}   -0.65{col 55}{space 3}0.516{col 63}{space 4}-.0494263{col 76}{space 3} .0248499
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3906559{col 35}{space 2} .0300648{col 46}{space 1}   12.99{col 55}{space 3}0.000{col 63}{space 4} .3315689{col 76}{space 3} .4497428
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_male
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if male==0, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2664
                                                       {txt}F( 35,   332) ={res}   10.61
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0954
                                                       {txt}Root MSE      = {res} .47879

{txt}{ralign 87:(Std. Err. adjusted for {res:333} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1101257{col 35}{space 2} .0216223{col 46}{space 1}    5.09{col 55}{space 3}0.000{col 63}{space 4} .0675916{col 76}{space 3} .1526597
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2}  .029841{col 35}{space 2} .0182964{col 46}{space 1}    1.63{col 55}{space 3}0.104{col 63}{space 4}-.0061506{col 76}{space 3} .0658325
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1282738{col 35}{space 2}  .023034{col 46}{space 1}   -5.57{col 55}{space 3}0.000{col 63}{space 4}-.1735847{col 76}{space 3}-.0829629
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1898283{col 35}{space 2} .0229745{col 46}{space 1}   -8.26{col 55}{space 3}0.000{col 63}{space 4}-.2350222{col 76}{space 3}-.1446345
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0849447{col 35}{space 2} .0317352{col 46}{space 1}    2.68{col 55}{space 3}0.008{col 63}{space 4} .0225173{col 76}{space 3} .1473721
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0731346{col 35}{space 2} .0303449{col 46}{space 1}    2.41{col 55}{space 3}0.016{col 63}{space 4} .0134421{col 76}{space 3}  .132827
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .161898{col 35}{space 2} .0295222{col 46}{space 1}    5.48{col 55}{space 3}0.000{col 63}{space 4} .1038239{col 76}{space 3}  .219972
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2112906{col 35}{space 2} .0307783{col 46}{space 1}    6.86{col 55}{space 3}0.000{col 63}{space 4} .1507455{col 76}{space 3} .2718356
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2234787{col 35}{space 2} .0246157{col 46}{space 1}    9.08{col 55}{space 3}0.000{col 63}{space 4} .1750563{col 76}{space 3}  .271901
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0281341{col 35}{space 2} .0243261{col 46}{space 1}    1.16{col 55}{space 3}0.248{col 63}{space 4}-.0197186{col 76}{space 3} .0759869
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2} -.010563{col 35}{space 2} .0141688{col 46}{space 1}   -0.75{col 55}{space 3}0.456{col 63}{space 4}-.0384349{col 76}{space 3} .0173088
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0250475{col 35}{space 2} .0262413{col 46}{space 1}   -0.95{col 55}{space 3}0.341{col 63}{space 4}-.0766676{col 76}{space 3} .0265727
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0194585{col 35}{space 2} .0145826{col 46}{space 1}   -1.33{col 55}{space 3}0.183{col 63}{space 4}-.0481443{col 76}{space 3} .0092274
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0133247{col 35}{space 2}  .016144{col 46}{space 1}   -0.83{col 55}{space 3}0.410{col 63}{space 4}-.0450822{col 76}{space 3} .0184328
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0100976{col 35}{space 2} .0137819{col 46}{space 1}   -0.73{col 55}{space 3}0.464{col 63}{space 4}-.0372085{col 76}{space 3} .0170132
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0323531{col 35}{space 2} .0250337{col 46}{space 1}   -1.29{col 55}{space 3}0.197{col 63}{space 4}-.0815978{col 76}{space 3} .0168916
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0395914{col 35}{space 2} .0261796{col 46}{space 1}   -1.51{col 55}{space 3}0.131{col 63}{space 4}-.0910901{col 76}{space 3} .0119074
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0346267{col 35}{space 2} .0259124{col 46}{space 1}   -1.34{col 55}{space 3}0.182{col 63}{space 4}-.0855999{col 76}{space 3} .0163464
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0206373{col 35}{space 2} .0268803{col 46}{space 1}   -0.77{col 55}{space 3}0.443{col 63}{space 4}-.0735145{col 76}{space 3} .0322399
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0146177{col 35}{space 2} .0214163{col 46}{space 1}   -0.68{col 55}{space 3}0.495{col 63}{space 4}-.0567465{col 76}{space 3} .0275111
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0132505{col 35}{space 2} .0219158{col 46}{space 1}    0.60{col 55}{space 3}0.546{col 63}{space 4}-.0298608{col 76}{space 3} .0563619
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0188035{col 35}{space 2} .0208873{col 46}{space 1}   -0.90{col 55}{space 3}0.369{col 63}{space 4}-.0598916{col 76}{space 3} .0222846
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0288608{col 35}{space 2} .0162175{col 46}{space 1}    1.78{col 55}{space 3}0.076{col 63}{space 4}-.0030412{col 76}{space 3} .0607628
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0193302{col 35}{space 2} .0263434{col 46}{space 1}   -0.73{col 55}{space 3}0.464{col 63}{space 4}-.0711513{col 76}{space 3} .0324909
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} .0072938{col 35}{space 2} .0174619{col 46}{space 1}    0.42{col 55}{space 3}0.676{col 63}{space 4}-.0270562{col 76}{space 3} .0416437
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0057788{col 35}{space 2} .0149269{col 46}{space 1}   -0.39{col 55}{space 3}0.699{col 63}{space 4} -.035142{col 76}{space 3} .0235843
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0208404{col 35}{space 2} .0187129{col 46}{space 1}    1.11{col 55}{space 3}0.266{col 63}{space 4}-.0159704{col 76}{space 3} .0576513
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0136896{col 35}{space 2} .0177954{col 46}{space 1}    0.77{col 55}{space 3}0.442{col 63}{space 4}-.0213164{col 76}{space 3} .0486956
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0274253{col 35}{space 2} .0220072{col 46}{space 1}   -1.25{col 55}{space 3}0.214{col 63}{space 4}-.0707164{col 76}{space 3} .0158657
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0294332{col 35}{space 2} .0188592{col 46}{space 1}    1.56{col 55}{space 3}0.120{col 63}{space 4}-.0076654{col 76}{space 3} .0665318
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0391602{col 35}{space 2} .0258174{col 46}{space 1}   -1.52{col 55}{space 3}0.130{col 63}{space 4}-.0899465{col 76}{space 3} .0116261
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0009242{col 35}{space 2} .0231797{col 46}{space 1}    0.04{col 55}{space 3}0.968{col 63}{space 4}-.0446734{col 76}{space 3} .0465219
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0105732{col 35}{space 2} .0220364{col 46}{space 1}    0.48{col 55}{space 3}0.632{col 63}{space 4}-.0327755{col 76}{space 3} .0539218
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} .0161063{col 35}{space 2} .0161967{col 46}{space 1}    0.99{col 55}{space 3}0.321{col 63}{space 4}-.0157548{col 76}{space 3} .0479673
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0225694{col 35}{space 2} .0174409{col 46}{space 1}    1.29{col 55}{space 3}0.197{col 63}{space 4}-.0117391{col 76}{space 3}  .056878
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3653165{col 35}{space 2} .0381429{col 46}{space 1}    9.58{col 55}{space 3}0.000{col 63}{space 4} .2902843{col 76}{space 3} .4403487
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_female
{txt}
{com}.         
.         coefplot (chosen_male, label(Male) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_female, label(Female) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_gend.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_gend.pdf written in PDF format)

{com}. 
.         
.         
. // FIGURE 11: Heterogeneity Results by Education
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if postsec_ed==1, cluster(pid)
{p 0 6 2}{txt}note: e_9 omitted because of collinearity{p_end}
{p 0 6 2}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_9 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}     576
                                                       {help j_robustsingular:F( 30,    71) =}       .
                                                       {txt}Prob > F      = {res}      .
                                                       {txt}R-squared     = {res} 0.1523
                                                       {txt}Root MSE      = {res} .47457

{txt}{ralign 87:(Std. Err. adjusted for {res:72} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0265453{col 35}{space 2} .0399102{col 46}{space 1}    0.67{col 55}{space 3}0.508{col 63}{space 4}-.0530333{col 76}{space 3}  .106124
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0491013{col 35}{space 2} .0416795{col 46}{space 1}    1.18{col 55}{space 3}0.243{col 63}{space 4}-.0340052{col 76}{space 3} .1322079
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2} -.192712{col 35}{space 2} .0554405{col 46}{space 1}   -3.48{col 55}{space 3}0.001{col 63}{space 4}-.3032572{col 76}{space 3}-.0821667
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1912556{col 35}{space 2} .0499467{col 46}{space 1}   -3.83{col 55}{space 3}0.000{col 63}{space 4}-.2908465{col 76}{space 3}-.0916646
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2}  .152834{col 35}{space 2} .0752666{col 46}{space 1}    2.03{col 55}{space 3}0.046{col 63}{space 4} .0027567{col 76}{space 3} .3029113
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .1895876{col 35}{space 2} .0685696{col 46}{space 1}    2.76{col 55}{space 3}0.007{col 63}{space 4} .0528638{col 76}{space 3} .3263114
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .246213{col 35}{space 2} .0783139{col 46}{space 1}    3.14{col 55}{space 3}0.002{col 63}{space 4} .0900595{col 76}{space 3} .4023664
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .4146688{col 35}{space 2} .0677908{col 46}{space 1}    6.12{col 55}{space 3}0.000{col 63}{space 4} .2794978{col 76}{space 3} .5498398
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2649649{col 35}{space 2} .0604134{col 46}{space 1}    4.39{col 55}{space 3}0.000{col 63}{space 4} .1445041{col 76}{space 3} .3854258
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} -.012522{col 35}{space 2} .0568319{col 46}{space 1}   -0.22{col 55}{space 3}0.826{col 63}{space 4}-.1258417{col 76}{space 3} .1007977
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2} .1385454{col 35}{space 2} .0451139{col 46}{space 1}    3.07{col 55}{space 3}0.003{col 63}{space 4} .0485908{col 76}{space 3} .2284999
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0668974{col 35}{space 2} .0636175{col 46}{space 1}   -1.05{col 55}{space 3}0.297{col 63}{space 4}-.1937471{col 76}{space 3} .0599524
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2} .1060843{col 35}{space 2} .0399132{col 46}{space 1}    2.66{col 55}{space 3}0.010{col 63}{space 4} .0264996{col 76}{space 3}  .185669
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .1159891{col 35}{space 2} .0379169{col 46}{space 1}    3.06{col 55}{space 3}0.003{col 63}{space 4} .0403849{col 76}{space 3} .1915934
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .1121481{col 35}{space 2} .0380079{col 46}{space 1}    2.95{col 55}{space 3}0.004{col 63}{space 4} .0363626{col 76}{space 3} .1879337
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2} .0298819{col 35}{space 2} .0455603{col 46}{space 1}    0.66{col 55}{space 3}0.514{col 63}{space 4}-.0609627{col 76}{space 3} .1207266
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}  .063022{col 35}{space 2} .0451728{col 46}{space 1}    1.40{col 55}{space 3}0.167{col 63}{space 4}  -.02705{col 76}{space 3} .1530941
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2} .1146753{col 35}{space 2} .0497807{col 46}{space 1}    2.30{col 55}{space 3}0.024{col 63}{space 4} .0154154{col 76}{space 3} .2139352
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0075878{col 35}{space 2} .0272181{col 46}{space 1}   -0.28{col 55}{space 3}0.781{col 63}{space 4}-.0618591{col 76}{space 3} .0466835
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2}-.0007101{col 35}{space 2} .0383155{col 46}{space 1}   -0.02{col 55}{space 3}0.985{col 63}{space 4} -.077109{col 76}{space 3} .0756889
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0023615{col 35}{space 2} .0297422{col 46}{space 1}   -0.08{col 55}{space 3}0.937{col 63}{space 4}-.0616658{col 76}{space 3} .0569428
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0850419{col 35}{space 2} .0502618{col 46}{space 1}    1.69{col 55}{space 3}0.095{col 63}{space 4}-.0151772{col 76}{space 3}  .185261
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0599451{col 35}{space 2} .0509308{col 46}{space 1}   -1.18{col 55}{space 3}0.243{col 63}{space 4}-.1614983{col 76}{space 3} .0416082
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} .0179133{col 35}{space 2} .0372612{col 46}{space 1}    0.48{col 55}{space 3}0.632{col 63}{space 4}-.0563833{col 76}{space 3}   .09221
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2} .0223393{col 35}{space 2} .0332529{col 46}{space 1}    0.67{col 55}{space 3}0.504{col 63}{space 4}-.0439651{col 76}{space 3} .0886436
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0455246{col 35}{space 2} .0399567{col 46}{space 1}    1.14{col 55}{space 3}0.258{col 63}{space 4}-.0341469{col 76}{space 3}  .125196
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0927799{col 35}{space 2} .0402045{col 46}{space 1}   -2.31{col 55}{space 3}0.024{col 63}{space 4}-.1729454{col 76}{space 3}-.0126144
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0720879{col 35}{space 2}  .040269{col 46}{space 1}    1.79{col 55}{space 3}0.078{col 63}{space 4}-.0082062{col 76}{space 3} .1523819
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}  .034608{col 35}{space 2} .0289681{col 46}{space 1}    1.19{col 55}{space 3}0.236{col 63}{space 4}-.0231526{col 76}{space 3} .0923687
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0714669{col 35}{space 2} .0310205{col 46}{space 1}   -2.30{col 55}{space 3}0.024{col 63}{space 4}  -.13332{col 76}{space 3}-.0096137
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0408656{col 35}{space 2} .0373741{col 46}{space 1}   -1.09{col 55}{space 3}0.278{col 63}{space 4}-.1153874{col 76}{space 3} .0336562
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} .0854085{col 35}{space 2} .0449529{col 46}{space 1}    1.90{col 55}{space 3}0.062{col 63}{space 4} -.004225{col 76}{space 3} .1750419
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0204355{col 35}{space 2} .0481498{col 46}{space 1}   -0.42{col 55}{space 3}0.673{col 63}{space 4}-.1164435{col 76}{space 3} .0755726
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .2215399{col 35}{space 2} .0831905{col 46}{space 1}    2.66{col 55}{space 3}0.010{col 63}{space 4} .0556627{col 76}{space 3} .3874171
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_uni
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if postsec_ed==0, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    5648
                                                       {txt}F( 35,   705) ={res}   19.11
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0930
                                                       {txt}Root MSE      = {res} .47771

{txt}{ralign 87:(Std. Err. adjusted for {res:706} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1072802{col 35}{space 2} .0147149{col 46}{space 1}    7.29{col 55}{space 3}0.000{col 63}{space 4} .0783899{col 76}{space 3} .1361705
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2}  .012582{col 35}{space 2} .0131713{col 46}{space 1}    0.96{col 55}{space 3}0.340{col 63}{space 4}-.0132777{col 76}{space 3} .0384418
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1409183{col 35}{space 2} .0165347{col 46}{space 1}   -8.52{col 55}{space 3}0.000{col 63}{space 4}-.1733815{col 76}{space 3}-.1084551
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1978454{col 35}{space 2} .0163713{col 46}{space 1}  -12.08{col 55}{space 3}0.000{col 63}{space 4}-.2299877{col 76}{space 3}-.1657032
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0774329{col 35}{space 2} .0217185{col 46}{space 1}    3.57{col 55}{space 3}0.000{col 63}{space 4} .0347921{col 76}{space 3} .1200736
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0794788{col 35}{space 2} .0211073{col 46}{space 1}    3.77{col 55}{space 3}0.000{col 63}{space 4} .0380381{col 76}{space 3} .1209195
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1234657{col 35}{space 2} .0205293{col 46}{space 1}    6.01{col 55}{space 3}0.000{col 63}{space 4}   .08316{col 76}{space 3} .1637715
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2328518{col 35}{space 2} .0213758{col 46}{space 1}   10.89{col 55}{space 3}0.000{col 63}{space 4} .1908839{col 76}{space 3} .2748198
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2}  .202508{col 35}{space 2} .0169787{col 46}{space 1}   11.93{col 55}{space 3}0.000{col 63}{space 4} .1691731{col 76}{space 3} .2358429
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0349792{col 35}{space 2}  .016777{col 46}{space 1}    2.08{col 55}{space 3}0.037{col 63}{space 4} .0020404{col 76}{space 3}  .067918
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0061348{col 35}{space 2}  .008285{col 46}{space 1}   -0.74{col 55}{space 3}0.459{col 63}{space 4} -.022401{col 76}{space 3} .0101314
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0008708{col 35}{space 2} .0154031{col 46}{space 1}   -0.06{col 55}{space 3}0.955{col 63}{space 4}-.0311123{col 76}{space 3} .0293707
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0172538{col 35}{space 2}  .008783{col 46}{space 1}   -1.96{col 55}{space 3}0.050{col 63}{space 4}-.0344977{col 76}{space 3}-9.84e-06
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0027904{col 35}{space 2}   .01046{col 46}{space 1}    0.27{col 55}{space 3}0.790{col 63}{space 4}-.0177462{col 76}{space 3}  .023327
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0000862{col 35}{space 2} .0088743{col 46}{space 1}   -0.01{col 55}{space 3}0.992{col 63}{space 4}-.0175094{col 76}{space 3} .0173371
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0100496{col 35}{space 2} .0148809{col 46}{space 1}   -0.68{col 55}{space 3}0.500{col 63}{space 4}-.0392659{col 76}{space 3} .0191666
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0100751{col 35}{space 2} .0155278{col 46}{space 1}   -0.65{col 55}{space 3}0.517{col 63}{space 4}-.0405614{col 76}{space 3} .0204112
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0106321{col 35}{space 2} .0153584{col 46}{space 1}   -0.69{col 55}{space 3}0.489{col 63}{space 4}-.0407858{col 76}{space 3} .0195215
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0025577{col 35}{space 2} .0154744{col 46}{space 1}   -0.17{col 55}{space 3}0.869{col 63}{space 4}-.0329392{col 76}{space 3} .0278238
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0294605{col 35}{space 2} .0136049{col 46}{space 1}   -2.17{col 55}{space 3}0.031{col 63}{space 4}-.0561714{col 76}{space 3}-.0027495
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0056047{col 35}{space 2} .0135937{col 46}{space 1}    0.41{col 55}{space 3}0.680{col 63}{space 4}-.0210843{col 76}{space 3} .0322936
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0158053{col 35}{space 2} .0122728{col 46}{space 1}   -1.29{col 55}{space 3}0.198{col 63}{space 4}-.0399009{col 76}{space 3} .0082903
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}  .005815{col 35}{space 2} .0126648{col 46}{space 1}    0.46{col 55}{space 3}0.646{col 63}{space 4}-.0190502{col 76}{space 3} .0306801
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0148304{col 35}{space 2} .0151328{col 46}{space 1}   -0.98{col 55}{space 3}0.327{col 63}{space 4}-.0445411{col 76}{space 3} .0148803
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0081043{col 35}{space 2} .0134124{col 46}{space 1}   -0.60{col 55}{space 3}0.546{col 63}{space 4}-.0344374{col 76}{space 3} .0182288
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0055162{col 35}{space 2} .0127186{col 46}{space 1}   -0.43{col 55}{space 3}0.665{col 63}{space 4}-.0304869{col 76}{space 3} .0194546
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0125647{col 35}{space 2} .0122569{col 46}{space 1}    1.03{col 55}{space 3}0.306{col 63}{space 4}-.0114997{col 76}{space 3} .0366291
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0000145{col 35}{space 2} .0131652{col 46}{space 1}   -0.00{col 55}{space 3}0.999{col 63}{space 4}-.0258622{col 76}{space 3} .0258331
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2} -.005198{col 35}{space 2} .0122938{col 46}{space 1}   -0.42{col 55}{space 3}0.673{col 63}{space 4}-.0293348{col 76}{space 3} .0189388
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}    .0057{col 35}{space 2} .0140178{col 46}{space 1}    0.41{col 55}{space 3}0.684{col 63}{space 4}-.0218217{col 76}{space 3} .0332217
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0114791{col 35}{space 2} .0131157{col 46}{space 1}   -0.88{col 55}{space 3}0.382{col 63}{space 4}-.0372296{col 76}{space 3} .0142714
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0060899{col 35}{space 2} .0130925{col 46}{space 1}    0.47{col 55}{space 3}0.642{col 63}{space 4}-.0196151{col 76}{space 3} .0317949
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0042721{col 35}{space 2} .0121261{col 46}{space 1}    0.35{col 55}{space 3}0.725{col 63}{space 4}-.0195355{col 76}{space 3} .0280796
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0077562{col 35}{space 2} .0129098{col 46}{space 1}   -0.60{col 55}{space 3}0.548{col 63}{space 4}-.0331024{col 76}{space 3}   .01759
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0046879{col 35}{space 2} .0130212{col 46}{space 1}    0.36{col 55}{space 3}0.719{col 63}{space 4} -.020877{col 76}{space 3} .0302528
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3816818{col 35}{space 2} .0249595{col 46}{space 1}   15.29{col 55}{space 3}0.000{col 63}{space 4}  .332678{col 76}{space 3} .4306857
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_nouni     
{txt}
{com}.         
.         coefplot (chosen_uni, label(University or Trade School) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_nouni, label(Secondary or less) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_ed.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_ed.pdf written in PDF format)

{com}.                 
.                 
.                 
. // FIGURE 12: Heterogeneity Results by Income 
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if weekly_profit<70000 & weekly_profit!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2504
                                                       {txt}F( 35,   312) ={res}    9.06
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0897
                                                       {txt}Root MSE      = {res} .48051

{txt}{ralign 87:(Std. Err. adjusted for {res:313} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1158998{col 35}{space 2} .0216657{col 46}{space 1}    5.35{col 55}{space 3}0.000{col 63}{space 4} .0732704{col 76}{space 3} .1585292
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0260974{col 35}{space 2} .0202774{col 46}{space 1}    1.29{col 55}{space 3}0.199{col 63}{space 4}-.0138004{col 76}{space 3} .0659951
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1529246{col 35}{space 2} .0250268{col 46}{space 1}   -6.11{col 55}{space 3}0.000{col 63}{space 4}-.2021671{col 76}{space 3} -.103682
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1839378{col 35}{space 2} .0249202{col 46}{space 1}   -7.38{col 55}{space 3}0.000{col 63}{space 4}-.2329707{col 76}{space 3}-.1349049
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0738784{col 35}{space 2} .0329336{col 46}{space 1}    2.24{col 55}{space 3}0.026{col 63}{space 4} .0090784{col 76}{space 3} .1386783
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0644024{col 35}{space 2} .0308492{col 46}{space 1}    2.09{col 55}{space 3}0.038{col 63}{space 4} .0037036{col 76}{space 3} .1251011
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1384401{col 35}{space 2} .0310562{col 46}{space 1}    4.46{col 55}{space 3}0.000{col 63}{space 4}  .077334{col 76}{space 3} .1995461
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2098653{col 35}{space 2} .0322203{col 46}{space 1}    6.51{col 55}{space 3}0.000{col 63}{space 4} .1464688{col 76}{space 3} .2732618
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2185521{col 35}{space 2} .0253253{col 46}{space 1}    8.63{col 55}{space 3}0.000{col 63}{space 4} .1687221{col 76}{space 3} .2683821
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0692918{col 35}{space 2} .0255198{col 46}{space 1}    2.72{col 55}{space 3}0.007{col 63}{space 4} .0190791{col 76}{space 3} .1195046
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0023267{col 35}{space 2} .0147506{col 46}{space 1}   -0.16{col 55}{space 3}0.875{col 63}{space 4}-.0313499{col 76}{space 3} .0266965
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2} .0088741{col 35}{space 2} .0203914{col 46}{space 1}    0.44{col 55}{space 3}0.664{col 63}{space 4} -.031248{col 76}{space 3} .0489962
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0147441{col 35}{space 2} .0142319{col 46}{space 1}   -1.04{col 55}{space 3}0.301{col 63}{space 4}-.0427467{col 76}{space 3} .0132584
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0293975{col 35}{space 2}  .015273{col 46}{space 1}    1.92{col 55}{space 3}0.055{col 63}{space 4}-.0006537{col 76}{space 3} .0594487
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0112621{col 35}{space 2} .0124826{col 46}{space 1}    0.90{col 55}{space 3}0.368{col 63}{space 4}-.0132986{col 76}{space 3} .0358227
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2} .0073569{col 35}{space 2} .0198846{col 46}{space 1}    0.37{col 55}{space 3}0.712{col 63}{space 4}-.0317679{col 76}{space 3} .0464817
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2} .0046613{col 35}{space 2} .0210685{col 46}{space 1}    0.22{col 55}{space 3}0.825{col 63}{space 4}-.0367929{col 76}{space 3} .0461156
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}   .00022{col 35}{space 2} .0211048{col 46}{space 1}    0.01{col 55}{space 3}0.992{col 63}{space 4}-.0413058{col 76}{space 3} .0417457
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2} .0199767{col 35}{space 2} .0213411{col 46}{space 1}    0.94{col 55}{space 3}0.350{col 63}{space 4} -.022014{col 76}{space 3} .0619674
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0310542{col 35}{space 2} .0190421{col 46}{space 1}   -1.63{col 55}{space 3}0.104{col 63}{space 4}-.0685214{col 76}{space 3}  .006413
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2}-.0069359{col 35}{space 2} .0212425{col 46}{space 1}   -0.33{col 55}{space 3}0.744{col 63}{space 4}-.0487326{col 76}{space 3} .0348609
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0252476{col 35}{space 2} .0157729{col 46}{space 1}   -1.60{col 55}{space 3}0.110{col 63}{space 4}-.0562823{col 76}{space 3} .0057871
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0135989{col 35}{space 2} .0183024{col 46}{space 1}    0.74{col 55}{space 3}0.458{col 63}{space 4}-.0224127{col 76}{space 3} .0496106
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2} .0081562{col 35}{space 2} .0166341{col 46}{space 1}    0.49{col 55}{space 3}0.624{col 63}{space 4} -.024573{col 76}{space 3} .0408854
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} -.003297{col 35}{space 2} .0185581{col 46}{space 1}   -0.18{col 55}{space 3}0.859{col 63}{space 4}-.0398119{col 76}{space 3} .0332179
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0051881{col 35}{space 2} .0175199{col 46}{space 1}   -0.30{col 55}{space 3}0.767{col 63}{space 4}-.0396602{col 76}{space 3}  .029284
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0159187{col 35}{space 2} .0184042{col 46}{space 1}    0.86{col 55}{space 3}0.388{col 63}{space 4}-.0202933{col 76}{space 3} .0521306
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0318434{col 35}{space 2} .0187823{col 46}{space 1}    1.70{col 55}{space 3}0.091{col 63}{space 4}-.0051125{col 76}{space 3} .0687993
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2} .0003258{col 35}{space 2} .0142479{col 46}{space 1}    0.02{col 55}{space 3}0.982{col 63}{space 4}-.0277083{col 76}{space 3} .0283599
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0082202{col 35}{space 2} .0220183{col 46}{space 1}    0.37{col 55}{space 3}0.709{col 63}{space 4} -.035103{col 76}{space 3} .0515433
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0263713{col 35}{space 2} .0249914{col 46}{space 1}   -1.06{col 55}{space 3}0.292{col 63}{space 4}-.0755444{col 76}{space 3} .0228018
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0145532{col 35}{space 2} .0175354{col 46}{space 1}    0.83{col 55}{space 3}0.407{col 63}{space 4}-.0199493{col 76}{space 3} .0490558
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0173189{col 35}{space 2} .0291553{col 46}{space 1}   -0.59{col 55}{space 3}0.553{col 63}{space 4}-.0746847{col 76}{space 3} .0400469
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0186231{col 35}{space 2} .0217369{col 46}{space 1}   -0.86{col 55}{space 3}0.392{col 63}{space 4}-.0613926{col 76}{space 3} .0241464
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0216392{col 35}{space 2} .0195976{col 46}{space 1}    1.10{col 55}{space 3}0.270{col 63}{space 4}-.0169209{col 76}{space 3} .0601993
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3426062{col 35}{space 2} .0350262{col 46}{space 1}    9.78{col 55}{space 3}0.000{col 63}{space 4} .2736889{col 76}{space 3} .4115236
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_L10
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if weekly_profit>=70000 & weekly_profit<140000 & weekly_profit!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    2096
                                                       {txt}F( 35,   261) ={res}    8.32
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1023
                                                       {txt}Root MSE      = {res} .47787

{txt}{ralign 87:(Std. Err. adjusted for {res:262} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1086525{col 35}{space 2} .0255032{col 46}{space 1}    4.26{col 55}{space 3}0.000{col 63}{space 4} .0584343{col 76}{space 3} .1588708
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0036892{col 35}{space 2} .0218673{col 46}{space 1}    0.17{col 55}{space 3}0.866{col 63}{space 4}-.0393696{col 76}{space 3} .0467481
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1146501{col 35}{space 2}  .027091{col 46}{space 1}   -4.23{col 55}{space 3}0.000{col 63}{space 4}-.1679947{col 76}{space 3}-.0613054
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1935523{col 35}{space 2} .0253877{col 46}{space 1}   -7.62{col 55}{space 3}0.000{col 63}{space 4} -.243543{col 76}{space 3}-.1435616
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .1109089{col 35}{space 2} .0362825{col 46}{space 1}    3.06{col 55}{space 3}0.002{col 63}{space 4} .0394653{col 76}{space 3} .1823526
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0815497{col 35}{space 2} .0359432{col 46}{space 1}    2.27{col 55}{space 3}0.024{col 63}{space 4} .0107742{col 76}{space 3} .1523253
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1172846{col 35}{space 2} .0334721{col 46}{space 1}    3.50{col 55}{space 3}0.001{col 63}{space 4} .0513748{col 76}{space 3} .1831943
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2826458{col 35}{space 2} .0338304{col 46}{space 1}    8.35{col 55}{space 3}0.000{col 63}{space 4} .2160305{col 76}{space 3} .3492611
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .1890783{col 35}{space 2} .0295889{col 46}{space 1}    6.39{col 55}{space 3}0.000{col 63}{space 4} .1308149{col 76}{space 3} .2473416
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0108467{col 35}{space 2} .0282443{col 46}{space 1}    0.38{col 55}{space 3}0.701{col 63}{space 4} -.044769{col 76}{space 3} .0664624
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0168534{col 35}{space 2} .0129874{col 46}{space 1}   -1.30{col 55}{space 3}0.196{col 63}{space 4}-.0424269{col 76}{space 3}   .00872
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0227724{col 35}{space 2} .0246455{col 46}{space 1}   -0.92{col 55}{space 3}0.356{col 63}{space 4}-.0713018{col 76}{space 3} .0257569
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0122982{col 35}{space 2} .0157102{col 46}{space 1}   -0.78{col 55}{space 3}0.434{col 63}{space 4} -.043233{col 76}{space 3} .0186366
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0247347{col 35}{space 2} .0167791{col 46}{space 1}   -1.47{col 55}{space 3}0.142{col 63}{space 4}-.0577744{col 76}{space 3}  .008305
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} -.002081{col 35}{space 2} .0142664{col 46}{space 1}   -0.15{col 55}{space 3}0.884{col 63}{space 4}-.0301728{col 76}{space 3} .0260108
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0544697{col 35}{space 2} .0267879{col 46}{space 1}   -2.03{col 55}{space 3}0.043{col 63}{space 4}-.1072176{col 76}{space 3}-.0017218
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0242617{col 35}{space 2} .0254057{col 46}{space 1}   -0.95{col 55}{space 3}0.340{col 63}{space 4}-.0742879{col 76}{space 3} .0257646
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0175147{col 35}{space 2} .0247381{col 46}{space 1}   -0.71{col 55}{space 3}0.480{col 63}{space 4}-.0662263{col 76}{space 3} .0311969
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0251211{col 35}{space 2} .0258509{col 46}{space 1}   -0.97{col 55}{space 3}0.332{col 63}{space 4} -.076024{col 76}{space 3} .0257819
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0221367{col 35}{space 2} .0188891{col 46}{space 1}   -1.17{col 55}{space 3}0.242{col 63}{space 4}-.0593311{col 76}{space 3} .0150577
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0071943{col 35}{space 2} .0200789{col 46}{space 1}    0.36{col 55}{space 3}0.720{col 63}{space 4}-.0323429{col 76}{space 3} .0467316
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0221604{col 35}{space 2} .0201854{col 46}{space 1}   -1.10{col 55}{space 3}0.273{col 63}{space 4}-.0619073{col 76}{space 3} .0175865
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0024926{col 35}{space 2} .0204153{col 46}{space 1}    0.12{col 55}{space 3}0.903{col 63}{space 4}-.0377071{col 76}{space 3} .0426923
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0666982{col 35}{space 2}  .030568{col 46}{space 1}   -2.18{col 55}{space 3}0.030{col 63}{space 4}-.1268895{col 76}{space 3}-.0065069
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0234442{col 35}{space 2} .0281464{col 46}{space 1}   -0.83{col 55}{space 3}0.406{col 63}{space 4}-.0788671{col 76}{space 3} .0319786
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0058878{col 35}{space 2}  .022141{col 46}{space 1}   -0.27{col 55}{space 3}0.791{col 63}{space 4}-.0494855{col 76}{space 3} .0377099
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0111546{col 35}{space 2} .0195444{col 46}{space 1}    0.57{col 55}{space 3}0.569{col 63}{space 4}-.0273301{col 76}{space 3} .0496393
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0170113{col 35}{space 2} .0217663{col 46}{space 1}   -0.78{col 55}{space 3}0.435{col 63}{space 4}-.0598712{col 76}{space 3} .0258487
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0068309{col 35}{space 2} .0228602{col 46}{space 1}   -0.30{col 55}{space 3}0.765{col 63}{space 4}-.0518448{col 76}{space 3}  .038183
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0031974{col 35}{space 2} .0248814{col 46}{space 1}    0.13{col 55}{space 3}0.898{col 63}{space 4}-.0457965{col 76}{space 3} .0521913
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0106757{col 35}{space 2} .0213754{col 46}{space 1}   -0.50{col 55}{space 3}0.618{col 63}{space 4}-.0527659{col 76}{space 3} .0314146
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0201387{col 35}{space 2} .0194837{col 46}{space 1}   -1.03{col 55}{space 3}0.302{col 63}{space 4}-.0585039{col 76}{space 3} .0182266
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0027956{col 35}{space 2} .0180685{col 46}{space 1}    0.15{col 55}{space 3}0.877{col 63}{space 4} -.032783{col 76}{space 3} .0383742
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0035019{col 35}{space 2} .0225659{col 46}{space 1}   -0.16{col 55}{space 3}0.877{col 63}{space 4}-.0479363{col 76}{space 3} .0409325
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0049099{col 35}{space 2} .0218233{col 46}{space 1}   -0.22{col 55}{space 3}0.822{col 63}{space 4}-.0478821{col 76}{space 3} .0380622
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3955506{col 35}{space 2} .0390425{col 46}{space 1}   10.13{col 55}{space 3}0.000{col 63}{space 4} .3186722{col 76}{space 3}  .472429
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_10_20
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if weekly_profit>=140000 & weekly_profit<210000 & weekly_profit!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}     800
                                                       {help j_robustsingular:F( 34,    99) =}       .
                                                       {txt}Prob > F      = {res}      .
                                                       {txt}R-squared     = {res} 0.1384
                                                       {txt}Root MSE      = {res} .47493

{txt}{ralign 87:(Std. Err. adjusted for {res:100} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0688862{col 35}{space 2} .0375858{col 46}{space 1}    1.83{col 55}{space 3}0.070{col 63}{space 4}-.0056923{col 76}{space 3} .1434646
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} -.026939{col 35}{space 2} .0357889{col 46}{space 1}   -0.75{col 55}{space 3}0.453{col 63}{space 4}-.0979519{col 76}{space 3} .0440739
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1675298{col 35}{space 2} .0483942{col 46}{space 1}   -3.46{col 55}{space 3}0.001{col 63}{space 4}-.2635544{col 76}{space 3}-.0715052
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2} -.229525{col 35}{space 2}  .049247{col 46}{space 1}   -4.66{col 55}{space 3}0.000{col 63}{space 4}-.3272416{col 76}{space 3}-.1318083
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .1338586{col 35}{space 2} .0552406{col 46}{space 1}    2.42{col 55}{space 3}0.017{col 63}{space 4} .0242492{col 76}{space 3}  .243468
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .1711102{col 35}{space 2} .0576706{col 46}{space 1}    2.97{col 55}{space 3}0.004{col 63}{space 4} .0566793{col 76}{space 3} .2855411
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .226145{col 35}{space 2} .0585089{col 46}{space 1}    3.87{col 55}{space 3}0.000{col 63}{space 4} .1100507{col 76}{space 3} .3422394
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .3136139{col 35}{space 2} .0638355{col 46}{space 1}    4.91{col 55}{space 3}0.000{col 63}{space 4} .1869503{col 76}{space 3} .4402774
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2640141{col 35}{space 2} .0467377{col 46}{space 1}    5.65{col 55}{space 3}0.000{col 63}{space 4} .1712763{col 76}{space 3} .3567519
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0182359{col 35}{space 2} .0450227{col 46}{space 1}    0.41{col 55}{space 3}0.686{col 63}{space 4} -.071099{col 76}{space 3} .1075707
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2} .0071592{col 35}{space 2} .0204304{col 46}{space 1}    0.35{col 55}{space 3}0.727{col 63}{space 4}-.0333791{col 76}{space 3} .0476975
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2} .0333366{col 35}{space 2} .0447852{col 46}{space 1}    0.74{col 55}{space 3}0.458{col 63}{space 4}-.0555269{col 76}{space 3} .1222002
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2} .0327312{col 35}{space 2} .0214877{col 46}{space 1}    1.52{col 55}{space 3}0.131{col 63}{space 4}-.0099051{col 76}{space 3} .0753674
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0042812{col 35}{space 2} .0226379{col 46}{space 1}    0.19{col 55}{space 3}0.850{col 63}{space 4}-.0406372{col 76}{space 3} .0491997
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2} .0069539{col 35}{space 2} .0264082{col 46}{space 1}    0.26{col 55}{space 3}0.793{col 63}{space 4}-.0454458{col 76}{space 3} .0593535
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0063245{col 35}{space 2}  .030715{col 46}{space 1}   -0.21{col 55}{space 3}0.837{col 63}{space 4}-.0672696{col 76}{space 3} .0546207
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0267088{col 35}{space 2} .0398832{col 46}{space 1}   -0.67{col 55}{space 3}0.505{col 63}{space 4}-.1058457{col 76}{space 3} .0524281
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0733748{col 35}{space 2} .0487906{col 46}{space 1}   -1.50{col 55}{space 3}0.136{col 63}{space 4} -.170186{col 76}{space 3} .0234364
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0153034{col 35}{space 2}  .043721{col 46}{space 1}   -0.35{col 55}{space 3}0.727{col 63}{space 4}-.1020553{col 76}{space 3} .0714485
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0089359{col 35}{space 2} .0253401{col 46}{space 1}   -0.35{col 55}{space 3}0.725{col 63}{space 4}-.0592162{col 76}{space 3} .0413444
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0149898{col 35}{space 2} .0258309{col 46}{space 1}    0.58{col 55}{space 3}0.563{col 63}{space 4}-.0362643{col 76}{space 3} .0662439
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}  .001412{col 35}{space 2} .0290148{col 46}{space 1}    0.05{col 55}{space 3}0.961{col 63}{space 4}-.0561597{col 76}{space 3} .0589838
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.0029183{col 35}{space 2} .0367511{col 46}{space 1}   -0.08{col 55}{space 3}0.937{col 63}{space 4}-.0758405{col 76}{space 3} .0700039
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2} .0222808{col 35}{space 2} .0422287{col 46}{space 1}    0.53{col 55}{space 3}0.599{col 63}{space 4}  -.06151{col 76}{space 3} .1060717
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}  .036186{col 35}{space 2} .0641147{col 46}{space 1}    0.56{col 55}{space 3}0.574{col 63}{space 4}-.0910315{col 76}{space 3} .1634036
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2} .0231373{col 35}{space 2} .0591497{col 46}{space 1}    0.39{col 55}{space 3}0.697{col 63}{space 4}-.0942286{col 76}{space 3} .1405033
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0669147{col 35}{space 2} .0408542{col 46}{space 1}    1.64{col 55}{space 3}0.105{col 63}{space 4}-.0141488{col 76}{space 3} .1479782
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} -.032737{col 35}{space 2} .0353013{col 46}{space 1}   -0.93{col 55}{space 3}0.356{col 63}{space 4}-.1027824{col 76}{space 3} .0373085
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0010359{col 35}{space 2} .0407554{col 46}{space 1}   -0.03{col 55}{space 3}0.980{col 63}{space 4}-.0819036{col 76}{space 3} .0798317
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0432245{col 35}{space 2} .0383844{col 46}{space 1}    1.13{col 55}{space 3}0.263{col 63}{space 4}-.0329385{col 76}{space 3} .1193875
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2} .0094686{col 35}{space 2} .0266354{col 46}{space 1}    0.36{col 55}{space 3}0.723{col 63}{space 4}-.0433817{col 76}{space 3} .0623189
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0465287{col 35}{space 2} .0294048{col 46}{space 1}    1.58{col 55}{space 3}0.117{col 63}{space 4}-.0118168{col 76}{space 3} .1048742
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0317576{col 35}{space 2} .0203198{col 46}{space 1}   -1.56{col 55}{space 3}0.121{col 63}{space 4}-.0720764{col 76}{space 3} .0085612
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} .0273587{col 35}{space 2} .0402967{col 46}{space 1}    0.68{col 55}{space 3}0.499{col 63}{space 4}-.0525986{col 76}{space 3} .1073161
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0075722{col 35}{space 2} .0417889{col 46}{space 1}    0.18{col 55}{space 3}0.857{col 63}{space 4} -.075346{col 76}{space 3} .0904905
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3468531{col 35}{space 2} .0693241{col 46}{space 1}    5.00{col 55}{space 3}0.000{col 63}{space 4} .2092991{col 76}{space 3} .4844071
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_20_30
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if weekly_profit>=210000 & weekly_profit!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}     824
                                                       {help j_robustsingular:F( 33,   102) =}       .
                                                       {txt}Prob > F      = {res}      .
                                                       {txt}R-squared     = {res} 0.0986
                                                       {txt}Root MSE      = {res} .48544

{txt}{ralign 87:(Std. Err. adjusted for {res:103} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0630313{col 35}{space 2} .0361695{col 46}{space 1}    1.74{col 55}{space 3}0.084{col 63}{space 4}-.0087108{col 76}{space 3} .1347735
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0544625{col 35}{space 2} .0321946{col 46}{space 1}    1.69{col 55}{space 3}0.094{col 63}{space 4}-.0093954{col 76}{space 3} .1183203
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1889446{col 35}{space 2} .0435585{col 46}{space 1}   -4.34{col 55}{space 3}0.000{col 63}{space 4}-.2753426{col 76}{space 3}-.1025467
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2282411{col 35}{space 2} .0452195{col 46}{space 1}   -5.05{col 55}{space 3}0.000{col 63}{space 4}-.3179337{col 76}{space 3}-.1385484
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0132964{col 35}{space 2} .0629965{col 46}{space 1}    0.21{col 55}{space 3}0.833{col 63}{space 4}-.1116568{col 76}{space 3} .1382496
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0839143{col 35}{space 2} .0604319{col 46}{space 1}    1.39{col 55}{space 3}0.168{col 63}{space 4} -.035952{col 76}{space 3} .2037806
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}    .0851{col 35}{space 2} .0603348{col 46}{space 1}    1.41{col 55}{space 3}0.161{col 63}{space 4}-.0345739{col 76}{space 3} .2047739
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2}  .233962{col 35}{space 2} .0597457{col 46}{space 1}    3.92{col 55}{space 3}0.000{col 63}{space 4} .1154566{col 76}{space 3} .3524673
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .1939146{col 35}{space 2} .0468176{col 46}{space 1}    4.14{col 55}{space 3}0.000{col 63}{space 4} .1010522{col 76}{space 3}  .286777
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} -.017001{col 35}{space 2} .0444738{col 46}{space 1}   -0.38{col 55}{space 3}0.703{col 63}{space 4}-.1052145{col 76}{space 3} .0712125
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0154715{col 35}{space 2} .0395327{col 46}{space 1}   -0.39{col 55}{space 3}0.696{col 63}{space 4}-.0938844{col 76}{space 3} .0629415
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0532501{col 35}{space 2} .0735218{col 46}{space 1}   -0.72{col 55}{space 3}0.471{col 63}{space 4}-.1990802{col 76}{space 3}   .09258
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2} -.026146{col 35}{space 2} .0268491{col 46}{space 1}   -0.97{col 55}{space 3}0.332{col 63}{space 4}-.0794011{col 76}{space 3}  .027109
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0501588{col 35}{space 2} .0321093{col 46}{space 1}    1.56{col 55}{space 3}0.121{col 63}{space 4}-.0135299{col 76}{space 3} .1138475
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0017003{col 35}{space 2} .0298734{col 46}{space 1}   -0.06{col 55}{space 3}0.955{col 63}{space 4} -.060954{col 76}{space 3} .0575534
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}  .065663{col 35}{space 2} .0458189{col 46}{space 1}    1.43{col 55}{space 3}0.155{col 63}{space 4}-.0252186{col 76}{space 3} .1565446
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2} .0153212{col 35}{space 2} .0511207{col 46}{space 1}    0.30{col 55}{space 3}0.765{col 63}{space 4}-.0860765{col 76}{space 3} .1167189
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2} .0056618{col 35}{space 2} .0491681{col 46}{space 1}    0.12{col 55}{space 3}0.909{col 63}{space 4}-.0918628{col 76}{space 3} .1031864
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2} .0283967{col 35}{space 2} .0451415{col 46}{space 1}    0.63{col 55}{space 3}0.531{col 63}{space 4}-.0611412{col 76}{space 3} .1179347
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2} .0274475{col 35}{space 2} .0220805{col 46}{space 1}    1.24{col 55}{space 3}0.217{col 63}{space 4}-.0163491{col 76}{space 3} .0712441
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0340814{col 35}{space 2} .0206507{col 46}{space 1}    1.65{col 55}{space 3}0.102{col 63}{space 4}-.0068791{col 76}{space 3} .0750419
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0112888{col 35}{space 2} .0339647{col 46}{space 1}   -0.33{col 55}{space 3}0.740{col 63}{space 4}-.0786577{col 76}{space 3} .0560801
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0340774{col 35}{space 2} .0443506{col 46}{space 1}    0.77{col 55}{space 3}0.444{col 63}{space 4}-.0538917{col 76}{space 3} .1220465
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0351115{col 35}{space 2} .0677758{col 46}{space 1}   -0.52{col 55}{space 3}0.606{col 63}{space 4}-.1695445{col 76}{space 3} .0993215
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} .0033346{col 35}{space 2}  .043121{col 46}{space 1}    0.08{col 55}{space 3}0.939{col 63}{space 4}-.0821957{col 76}{space 3} .0888649
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0362999{col 35}{space 2} .0462599{col 46}{space 1}   -0.78{col 55}{space 3}0.434{col 63}{space 4}-.1280562{col 76}{space 3} .0554565
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0099401{col 35}{space 2} .0402997{col 46}{space 1}    0.25{col 55}{space 3}0.806{col 63}{space 4}-.0699941{col 76}{space 3} .0898744
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0340485{col 35}{space 2} .0528344{col 46}{space 1}    0.64{col 55}{space 3}0.521{col 63}{space 4}-.0707484{col 76}{space 3} .1388454
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2} .0109367{col 35}{space 2} .0465838{col 46}{space 1}    0.23{col 55}{space 3}0.815{col 63}{space 4}-.0814619{col 76}{space 3} .1033354
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}-.0481684{col 35}{space 2} .0381425{col 46}{space 1}   -1.26{col 55}{space 3}0.210{col 63}{space 4}-.1238237{col 76}{space 3}  .027487
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2} .0035406{col 35}{space 2} .0208479{col 46}{space 1}    0.17{col 55}{space 3}0.865{col 63}{space 4}-.0378112{col 76}{space 3} .0448923
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0234044{col 35}{space 2} .0343298{col 46}{space 1}    0.68{col 55}{space 3}0.497{col 63}{space 4}-.0446885{col 76}{space 3} .0914973
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0088857{col 35}{space 2} .0256069{col 46}{space 1}    0.35{col 55}{space 3}0.729{col 63}{space 4}-.0419054{col 76}{space 3} .0596767
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} -.015785{col 35}{space 2}   .03589{col 46}{space 1}   -0.44{col 55}{space 3}0.661{col 63}{space 4}-.0869727{col 76}{space 3} .0554026
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0440631{col 35}{space 2} .0397266{col 46}{space 1}   -1.11{col 55}{space 3}0.270{col 63}{space 4}-.1228606{col 76}{space 3} .0347344
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .4338742{col 35}{space 2} .0608695{col 46}{space 1}    7.13{col 55}{space 3}0.000{col 63}{space 4} .3131398{col 76}{space 3} .5546086
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_G30
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if weekly_profit>=70000 & weekly_profit!=., cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    3720
                                                       {txt}F( 35,   464) ={res}   13.97
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1034
                                                       {txt}Root MSE      = {res} .47574

{txt}{ralign 87:(Std. Err. adjusted for {res:465} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2}    .0876{col 35}{space 2} .0180062{col 46}{space 1}    4.86{col 55}{space 3}0.000{col 63}{space 4} .0522162{col 76}{space 3} .1229838
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0091285{col 35}{space 2} .0159689{col 46}{space 1}    0.57{col 55}{space 3}0.568{col 63}{space 4}-.0222518{col 76}{space 3} .0405087
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2} -.140347{col 35}{space 2} .0203527{col 46}{space 1}   -6.90{col 55}{space 3}0.000{col 63}{space 4}-.1803418{col 76}{space 3}-.1003522
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.2078085{col 35}{space 2} .0197998{col 46}{space 1}  -10.50{col 55}{space 3}0.000{col 63}{space 4}-.2467168{col 76}{space 3}-.1689002
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0924253{col 35}{space 2} .0270848{col 46}{space 1}    3.41{col 55}{space 3}0.001{col 63}{space 4} .0392012{col 76}{space 3} .1456495
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .1023569{col 35}{space 2} .0266144{col 46}{space 1}    3.85{col 55}{space 3}0.000{col 63}{space 4} .0500572{col 76}{space 3} .1546565
{txt}{space 11}Education  {c |}{col 23}{res}{space 2}  .131297{col 35}{space 2} .0257578{col 46}{space 1}    5.10{col 55}{space 3}0.000{col 63}{space 4} .0806806{col 76}{space 3} .1819135
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2748946{col 35}{space 2} .0262808{col 46}{space 1}   10.46{col 55}{space 3}0.000{col 63}{space 4} .2232504{col 76}{space 3} .3265387
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2028227{col 35}{space 2} .0217307{col 46}{space 1}    9.33{col 55}{space 3}0.000{col 63}{space 4} .1601199{col 76}{space 3} .2455256
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0038574{col 35}{space 2} .0206857{col 46}{space 1}    0.19{col 55}{space 3}0.852{col 63}{space 4}-.0367919{col 76}{space 3} .0445067
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0089289{col 35}{space 2} .0094499{col 46}{space 1}   -0.94{col 55}{space 3}0.345{col 63}{space 4}-.0274988{col 76}{space 3}  .009641
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0127941{col 35}{space 2} .0214441{col 46}{space 1}   -0.60{col 55}{space 3}0.551{col 63}{space 4}-.0549337{col 76}{space 3} .0293455
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0154031{col 35}{space 2} .0100875{col 46}{space 1}   -1.53{col 55}{space 3}0.127{col 63}{space 4}-.0352259{col 76}{space 3} .0044197
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0077496{col 35}{space 2} .0120967{col 46}{space 1}   -0.64{col 55}{space 3}0.522{col 63}{space 4}-.0315208{col 76}{space 3} .0160216
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0018454{col 35}{space 2} .0104419{col 46}{space 1}   -0.18{col 55}{space 3}0.860{col 63}{space 4}-.0223647{col 76}{space 3}  .018674
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2} -.027352{col 35}{space 2} .0184631{col 46}{space 1}   -1.48{col 55}{space 3}0.139{col 63}{space 4}-.0636337{col 76}{space 3} .0089297
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0106064{col 35}{space 2} .0191921{col 46}{space 1}   -0.55{col 55}{space 3}0.581{col 63}{space 4}-.0483206{col 76}{space 3} .0271078
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0183295{col 35}{space 2} .0192467{col 46}{space 1}   -0.95{col 55}{space 3}0.341{col 63}{space 4} -.056151{col 76}{space 3} .0194919
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0067852{col 35}{space 2} .0192013{col 46}{space 1}   -0.35{col 55}{space 3}0.724{col 63}{space 4}-.0445174{col 76}{space 3}  .030947
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0060695{col 35}{space 2} .0140179{col 46}{space 1}   -0.43{col 55}{space 3}0.665{col 63}{space 4}-.0336159{col 76}{space 3} .0214769
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0109089{col 35}{space 2} .0141699{col 46}{space 1}    0.77{col 55}{space 3}0.442{col 63}{space 4}-.0169362{col 76}{space 3} .0387539
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0082479{col 35}{space 2}  .014517{col 46}{space 1}   -0.57{col 55}{space 3}0.570{col 63}{space 4}-.0367751{col 76}{space 3} .0202793
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2}-.0024525{col 35}{space 2} .0167129{col 46}{space 1}   -0.15{col 55}{space 3}0.883{col 63}{space 4}-.0352949{col 76}{space 3} .0303899
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0401886{col 35}{space 2}  .023757{col 46}{space 1}   -1.69{col 55}{space 3}0.091{col 63}{space 4}-.0868732{col 76}{space 3}  .006496
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0129517{col 35}{space 2} .0188325{col 46}{space 1}   -0.69{col 55}{space 3}0.492{col 63}{space 4}-.0499593{col 76}{space 3} .0240559
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0106404{col 35}{space 2} .0175825{col 46}{space 1}   -0.61{col 55}{space 3}0.545{col 63}{space 4}-.0451915{col 76}{space 3} .0239107
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0049682{col 35}{space 2} .0159374{col 46}{space 1}    0.31{col 55}{space 3}0.755{col 63}{space 4}-.0263501{col 76}{space 3} .0362865
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0221015{col 35}{space 2}  .017096{col 46}{space 1}   -1.29{col 55}{space 3}0.197{col 63}{space 4}-.0556966{col 76}{space 3} .0114937
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0056015{col 35}{space 2} .0175364{col 46}{space 1}   -0.32{col 55}{space 3}0.750{col 63}{space 4}-.0400621{col 76}{space 3} .0288591
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0036485{col 35}{space 2} .0179045{col 46}{space 1}    0.20{col 55}{space 3}0.839{col 63}{space 4}-.0315356{col 76}{space 3} .0388325
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0051015{col 35}{space 2} .0142145{col 46}{space 1}   -0.36{col 55}{space 3}0.720{col 63}{space 4}-.0330342{col 76}{space 3} .0228313
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0031639{col 35}{space 2} .0154455{col 46}{space 1}   -0.20{col 55}{space 3}0.838{col 63}{space 4}-.0335157{col 76}{space 3}  .027188
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2}-.0038719{col 35}{space 2} .0131315{col 46}{space 1}   -0.29{col 55}{space 3}0.768{col 63}{space 4}-.0296764{col 76}{space 3} .0219326
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2}-.0041789{col 35}{space 2} .0162124{col 46}{space 1}   -0.26{col 55}{space 3}0.797{col 63}{space 4}-.0360378{col 76}{space 3}   .02768
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} -.012036{col 35}{space 2} .0168826{col 46}{space 1}   -0.71{col 55}{space 3}0.476{col 63}{space 4}-.0452119{col 76}{space 3} .0211399
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3975429{col 35}{space 2} .0301223{col 46}{space 1}   13.20{col 55}{space 3}0.000{col 63}{space 4} .3383499{col 76}{space 3} .4567359
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_G10
{txt}
{com}.                 
.         * Output for left-hand panel of figure
.         coefplot (chosen_L10, label(Less than 10K a Day) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_10_20, label(10-20K a day) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_inc1.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_inc1.pdf written in PDF format)

{com}.         
.         * Output for right-hand panel of figure
.         coefplot (chosen_20_30, label(20K-30K a day) msymbol(triangle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)) ///
>                 (chosen_G30, label(30K+ a day) msymbol(diamond) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_inc2.pdf", as(pdf) replace     
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_inc2.pdf written in PDF format)

{com}.                 
.                 
.                 
. // FIGURE 13: Heterogeneity Results by Urban/Rural 
. 
.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if urban_dum==1, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    4496
                                                       {txt}F( 35,   561) ={res}   15.24
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0886
                                                       {txt}Root MSE      = {res} .47926

{txt}{ralign 87:(Std. Err. adjusted for {res:562} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .0842379{col 35}{space 2} .0161959{col 46}{space 1}    5.20{col 55}{space 3}0.000{col 63}{space 4} .0524259{col 76}{space 3}   .11605
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0040188{col 35}{space 2} .0150537{col 46}{space 1}    0.27{col 55}{space 3}0.790{col 63}{space 4}-.0255498{col 76}{space 3} .0335873
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1388652{col 35}{space 2} .0185423{col 46}{space 1}   -7.49{col 55}{space 3}0.000{col 63}{space 4}-.1752861{col 76}{space 3}-.1024444
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1994348{col 35}{space 2} .0176144{col 46}{space 1}  -11.32{col 55}{space 3}0.000{col 63}{space 4}-.2340331{col 76}{space 3}-.1648365
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2}   .09926{col 35}{space 2} .0250759{col 46}{space 1}    3.96{col 55}{space 3}0.000{col 63}{space 4} .0500058{col 76}{space 3} .1485142
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .1034391{col 35}{space 2}  .024012{col 46}{space 1}    4.31{col 55}{space 3}0.000{col 63}{space 4} .0562747{col 76}{space 3} .1506035
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1347917{col 35}{space 2} .0239013{col 46}{space 1}    5.64{col 55}{space 3}0.000{col 63}{space 4} .0878447{col 76}{space 3} .1817387
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2566692{col 35}{space 2} .0247771{col 46}{space 1}   10.36{col 55}{space 3}0.000{col 63}{space 4} .2080019{col 76}{space 3} .3053366
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .1881144{col 35}{space 2} .0194911{col 46}{space 1}    9.65{col 55}{space 3}0.000{col 63}{space 4}   .14983{col 76}{space 3} .2263989
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0155471{col 35}{space 2}  .019142{col 46}{space 1}    0.81{col 55}{space 3}0.417{col 63}{space 4}-.0220517{col 76}{space 3}  .053146
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0026611{col 35}{space 2} .0088813{col 46}{space 1}   -0.30{col 55}{space 3}0.765{col 63}{space 4}-.0201057{col 76}{space 3} .0147835
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2} .0022051{col 35}{space 2} .0167539{col 46}{space 1}    0.13{col 55}{space 3}0.895{col 63}{space 4}-.0307029{col 76}{space 3} .0351131
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0064066{col 35}{space 2} .0098133{col 46}{space 1}   -0.65{col 55}{space 3}0.514{col 63}{space 4} -.025682{col 76}{space 3} .0128688
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2} .0092146{col 35}{space 2} .0120003{col 46}{space 1}    0.77{col 55}{space 3}0.443{col 63}{space 4}-.0143563{col 76}{space 3} .0327856
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}  .011375{col 35}{space 2} .0094077{col 46}{space 1}    1.21{col 55}{space 3}0.227{col 63}{space 4}-.0071037{col 76}{space 3} .0298536
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0034667{col 35}{space 2} .0159814{col 46}{space 1}   -0.22{col 55}{space 3}0.828{col 63}{space 4}-.0348573{col 76}{space 3} .0279239
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0053583{col 35}{space 2} .0171334{col 46}{space 1}   -0.31{col 55}{space 3}0.755{col 63}{space 4}-.0390118{col 76}{space 3} .0282951
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0093951{col 35}{space 2}  .017048{col 46}{space 1}   -0.55{col 55}{space 3}0.582{col 63}{space 4}-.0428807{col 76}{space 3} .0240906
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0071472{col 35}{space 2} .0173753{col 46}{space 1}   -0.41{col 55}{space 3}0.681{col 63}{space 4}-.0412758{col 76}{space 3} .0269814
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2}-.0311846{col 35}{space 2} .0127498{col 46}{space 1}   -2.45{col 55}{space 3}0.015{col 63}{space 4}-.0562278{col 76}{space 3}-.0061414
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2}-.0005142{col 35}{space 2} .0131296{col 46}{space 1}   -0.04{col 55}{space 3}0.969{col 63}{space 4}-.0263034{col 76}{space 3}  .025275
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2}-.0149912{col 35}{space 2} .0140846{col 46}{space 1}   -1.06{col 55}{space 3}0.288{col 63}{space 4}-.0426563{col 76}{space 3} .0126739
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0005178{col 35}{space 2} .0141576{col 46}{space 1}    0.04{col 55}{space 3}0.971{col 63}{space 4}-.0272907{col 76}{space 3} .0283263
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2}-.0177041{col 35}{space 2} .0165685{col 46}{space 1}   -1.07{col 55}{space 3}0.286{col 63}{space 4}-.0502481{col 76}{space 3} .0148399
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2}-.0119958{col 35}{space 2} .0151586{col 46}{space 1}   -0.79{col 55}{space 3}0.429{col 63}{space 4}-.0417702{col 76}{space 3} .0177787
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2}-.0099468{col 35}{space 2} .0141694{col 46}{space 1}   -0.70{col 55}{space 3}0.483{col 63}{space 4}-.0377784{col 76}{space 3} .0178848
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2}-.0038948{col 35}{space 2} .0152323{col 46}{space 1}   -0.26{col 55}{space 3}0.798{col 63}{space 4}-.0338141{col 76}{space 3} .0260245
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2}-.0012942{col 35}{space 2} .0151854{col 46}{space 1}   -0.09{col 55}{space 3}0.932{col 63}{space 4}-.0311214{col 76}{space 3} .0285329
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}-.0171635{col 35}{space 2} .0115423{col 46}{space 1}   -1.49{col 55}{space 3}0.138{col 63}{space 4}-.0398349{col 76}{space 3} .0055078
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2}  .006952{col 35}{space 2} .0201005{col 46}{space 1}    0.35{col 55}{space 3}0.730{col 63}{space 4}-.0325294{col 76}{space 3} .0464335
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2}-.0145898{col 35}{space 2} .0128585{col 46}{space 1}   -1.13{col 55}{space 3}0.257{col 63}{space 4}-.0398466{col 76}{space 3}  .010667
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2}-.0066407{col 35}{space 2} .0127187{col 46}{space 1}   -0.52{col 55}{space 3}0.602{col 63}{space 4}-.0316227{col 76}{space 3} .0183413
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0001497{col 35}{space 2} .0130383{col 46}{space 1}    0.01{col 55}{space 3}0.991{col 63}{space 4}-.0254602{col 76}{space 3} .0257596
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} -.016529{col 35}{space 2} .0152474{col 46}{space 1}   -1.08{col 55}{space 3}0.279{col 63}{space 4}-.0464779{col 76}{space 3}   .01342
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2}-.0028105{col 35}{space 2} .0157164{col 46}{space 1}   -0.18{col 55}{space 3}0.858{col 63}{space 4}-.0336807{col 76}{space 3} .0280597
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3947936{col 35}{space 2} .0277215{col 46}{space 1}   14.24{col 55}{space 3}0.000{col 63}{space 4} .3403429{col 76}{space 3} .4492443
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_urban
{txt}
{com}.         reg chosen i.att1 i.att2 i.att4 i.att5 i.att3 $fe $townfe if urban_dum==0, cluster(pid)
{p 0 6 2}{txt}note: e_10 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_17 omitted because of collinearity{p_end}
{p 0 6 2}note: townfe_18 omitted because of collinearity{p_end}

Linear regression                                      Number of obs ={res}    1712
                                                       {txt}F( 35,   213) ={res}    8.69
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1215
                                                       {txt}Root MSE      = {res} .47364

{txt}{ralign 87:(Std. Err. adjusted for {res:214} clusters in pid)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}               chosen{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}att1 {c |}
{space 13}Elected  {c |}{col 23}{res}{space 2} .1385485{col 35}{space 2} .0269851{col 46}{space 1}    5.13{col 55}{space 3}0.000{col 63}{space 4} .0853564{col 76}{space 3} .1917406
{txt}{space 21} {c |}
{space 17}att2 {c |}
{space 13}Central  {c |}{col 23}{res}{space 2} .0482057{col 35}{space 2} .0222272{col 46}{space 1}    2.17{col 55}{space 3}0.031{col 63}{space 4} .0043923{col 76}{space 3} .0920191
{txt}{space 21} {c |}
{space 17}att4 {c |}
{space 9}Clientelism  {c |}{col 23}{res}{space 2}-.1630619{col 35}{space 2} .0306115{col 46}{space 1}   -5.33{col 55}{space 3}0.000{col 63}{space 4}-.2234021{col 76}{space 3}-.1027217
{txt}{space 11}Patronage  {c |}{col 23}{res}{space 2}-.1896852{col 35}{space 2} .0324238{col 46}{space 1}   -5.85{col 55}{space 3}0.000{col 63}{space 4}-.2535978{col 76}{space 3}-.1257726
{txt}{space 21} {c |}
{space 17}att5 {c |}
{space 15}Water  {c |}{col 23}{res}{space 2} .0445917{col 35}{space 2} .0370317{col 46}{space 1}    1.20{col 55}{space 3}0.230{col 63}{space 4}-.0284038{col 76}{space 3} .1175871
{txt}Infrastructure/Roads  {c |}{col 23}{res}{space 2} .0531683{col 35}{space 2} .0379534{col 46}{space 1}    1.40{col 55}{space 3}0.163{col 63}{space 4}-.0216442{col 76}{space 3} .1279807
{txt}{space 11}Education  {c |}{col 23}{res}{space 2} .1321464{col 35}{space 2} .0364037{col 46}{space 1}    3.63{col 55}{space 3}0.000{col 63}{space 4} .0603888{col 76}{space 3}  .203904
{txt}{space 9}Health Care  {c |}{col 23}{res}{space 2} .2153072{col 35}{space 2} .0351332{col 46}{space 1}    6.13{col 55}{space 3}0.000{col 63}{space 4} .1460539{col 76}{space 3} .2845606
{txt}{space 21} {c |}
{space 17}att3 {c |}
{space 17}Tax  {c |}{col 23}{res}{space 2} .2543425{col 35}{space 2}  .029758{col 46}{space 1}    8.55{col 55}{space 3}0.000{col 63}{space 4} .1956845{col 76}{space 3} .3130005
{txt}{space 11}Transfers  {c |}{col 23}{res}{space 2} .0706185{col 35}{space 2} .0298042{col 46}{space 1}    2.37{col 55}{space 3}0.019{col 63}{space 4} .0118695{col 76}{space 3} .1293674
{txt}{space 21} {c |}
{space 18}e_1 {c |}{col 23}{res}{space 2}-.0302922{col 35}{space 2} .0215879{col 46}{space 1}   -1.40{col 55}{space 3}0.162{col 63}{space 4}-.0728456{col 76}{space 3} .0122611
{txt}{space 18}e_2 {c |}{col 23}{res}{space 2}-.0356011{col 35}{space 2} .0351194{col 46}{space 1}   -1.01{col 55}{space 3}0.312{col 63}{space 4}-.1048271{col 76}{space 3} .0336249
{txt}{space 18}e_3 {c |}{col 23}{res}{space 2}-.0441145{col 35}{space 2} .0167262{col 46}{space 1}   -2.64{col 55}{space 3}0.009{col 63}{space 4}-.0770846{col 76}{space 3}-.0111445
{txt}{space 18}e_4 {c |}{col 23}{res}{space 2}-.0246247{col 35}{space 2} .0200432{col 46}{space 1}   -1.23{col 55}{space 3}0.221{col 63}{space 4}-.0641331{col 76}{space 3} .0148836
{txt}{space 18}e_5 {c |}{col 23}{res}{space 2}-.0433498{col 35}{space 2} .0185516{col 46}{space 1}   -2.34{col 55}{space 3}0.020{col 63}{space 4}-.0799179{col 76}{space 3}-.0067816
{txt}{space 18}e_6 {c |}{col 23}{res}{space 2}-.0220742{col 35}{space 2} .0281571{col 46}{space 1}   -0.78{col 55}{space 3}0.434{col 63}{space 4}-.0775764{col 76}{space 3}  .033428
{txt}{space 18}e_7 {c |}{col 23}{res}{space 2}-.0164565{col 35}{space 2} .0274181{col 46}{space 1}   -0.60{col 55}{space 3}0.549{col 63}{space 4}-.0705021{col 76}{space 3} .0375891
{txt}{space 18}e_8 {c |}{col 23}{res}{space 2}-.0133421{col 35}{space 2} .0276918{col 46}{space 1}   -0.48{col 55}{space 3}0.630{col 63}{space 4}-.0679271{col 76}{space 3} .0412428
{txt}{space 18}e_9 {c |}{col 23}{res}{space 2}-.0001082{col 35}{space 2} .0282666{col 46}{space 1}   -0.00{col 55}{space 3}0.997{col 63}{space 4}-.0558264{col 76}{space 3}   .05561
{txt}{space 17}e_10 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 13}townfe_1 {c |}{col 23}{res}{space 2} .0384265{col 35}{space 2} .0242172{col 46}{space 1}    1.59{col 55}{space 3}0.114{col 63}{space 4}-.0093095{col 76}{space 3} .0861625
{txt}{space 13}townfe_2 {c |}{col 23}{res}{space 2} .0297682{col 35}{space 2} .0249887{col 46}{space 1}    1.19{col 55}{space 3}0.235{col 63}{space 4}-.0194886{col 76}{space 3} .0790249
{txt}{space 13}townfe_3 {c |}{col 23}{res}{space 2} .0119365{col 35}{space 2} .0178178{col 46}{space 1}    0.67{col 55}{space 3}0.504{col 63}{space 4}-.0231853{col 76}{space 3} .0470583
{txt}{space 13}townfe_4 {c |}{col 23}{res}{space 2} .0441041{col 35}{space 2} .0266399{col 46}{space 1}    1.66{col 55}{space 3}0.099{col 63}{space 4}-.0084076{col 76}{space 3} .0966158
{txt}{space 13}townfe_5 {c |}{col 23}{res}{space 2} .0081771{col 35}{space 2} .0269372{col 46}{space 1}    0.30{col 55}{space 3}0.762{col 63}{space 4}-.0449206{col 76}{space 3} .0612749
{txt}{space 13}townfe_6 {c |}{col 23}{res}{space 2} .0084865{col 35}{space 2} .0257719{col 46}{space 1}    0.33{col 55}{space 3}0.742{col 63}{space 4}-.0423142{col 76}{space 3} .0592872
{txt}{space 13}townfe_7 {c |}{col 23}{res}{space 2} .0093103{col 35}{space 2} .0317956{col 46}{space 1}    0.29{col 55}{space 3}0.770{col 63}{space 4}-.0533642{col 76}{space 3} .0719847
{txt}{space 13}townfe_8 {c |}{col 23}{res}{space 2} .0406272{col 35}{space 2} .0236245{col 46}{space 1}    1.72{col 55}{space 3}0.087{col 63}{space 4}-.0059406{col 76}{space 3} .0871951
{txt}{space 13}townfe_9 {c |}{col 23}{res}{space 2} .0042239{col 35}{space 2} .0303682{col 46}{space 1}    0.14{col 55}{space 3}0.890{col 63}{space 4}-.0556369{col 76}{space 3} .0640847
{txt}{space 12}townfe_10 {c |}{col 23}{res}{space 2}  .044198{col 35}{space 2} .0303745{col 46}{space 1}    1.46{col 55}{space 3}0.147{col 63}{space 4} -.015675{col 76}{space 3} .1040711
{txt}{space 12}townfe_11 {c |}{col 23}{res}{space 2} .0159094{col 35}{space 2} .0228344{col 46}{space 1}    0.70{col 55}{space 3}0.487{col 63}{space 4} -.029101{col 76}{space 3} .0609199
{txt}{space 12}townfe_12 {c |}{col 23}{res}{space 2} .0358822{col 35}{space 2} .0329668{col 46}{space 1}    1.09{col 55}{space 3}0.278{col 63}{space 4}-.0291008{col 76}{space 3} .1008653
{txt}{space 12}townfe_13 {c |}{col 23}{res}{space 2} .0253933{col 35}{space 2} .0339418{col 46}{space 1}    0.75{col 55}{space 3}0.455{col 63}{space 4}-.0415115{col 76}{space 3} .0922981
{txt}{space 12}townfe_14 {c |}{col 23}{res}{space 2} .0284829{col 35}{space 2} .0177788{col 46}{space 1}    1.60{col 55}{space 3}0.111{col 63}{space 4}-.0065619{col 76}{space 3} .0635278
{txt}{space 12}townfe_15 {c |}{col 23}{res}{space 2} .0126544{col 35}{space 2} .0243343{col 46}{space 1}    0.52{col 55}{space 3}0.604{col 63}{space 4}-.0353125{col 76}{space 3} .0606214
{txt}{space 12}townfe_16 {c |}{col 23}{res}{space 2} .0225621{col 35}{space 2} .0238302{col 46}{space 1}    0.95{col 55}{space 3}0.345{col 63}{space 4} -.024411{col 76}{space 3} .0695353
{txt}{space 12}townfe_17 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 12}townfe_18 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 16}_cons {c |}{col 23}{res}{space 2} .3270467{col 35}{space 2} .0418299{col 46}{space 1}    7.82{col 55}{space 3}0.000{col 63}{space 4} .2445931{col 76}{space 3} .4095003
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 estimate store chosen_rural
{txt}
{com}.         
.         coefplot (chosen_urban, label(Urban Resident) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3) )  ///
>                 (chosen_rural, label(Rural Resident) msymbol(circle_hollow) mcolor(black) msize(large) ciopts(lcolor(black) lwidth(thin)) xlabel(-.3(.1).3)), ///
>                 drop(_cons e_* $townfe ) omitted base xline(0)  ///
>                 headings(1.att1 = "{c -(}bf:Type of Official{c )-}" 1.att2 = "{c -(}bf:Level of Government{c )-}" 1.att3 = "{c -(}bf:Source of Funds{c )-}" 1.att4 = "{c -(}bf:How Funds Spent{c )-}" 1.att5 = "{c -(}bf:Funds Stolen From{c )-}" )  ///
>                 ylabel(, labsize(medlarge)) xtitle("Change in Pr(Official Selected)") ytitle("") xsize(5) ysize(7) scale(.6) 
{res}{txt}
{com}.         graph export "Tables/het_urban.pdf", as(pdf) replace
{txt}(file /Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Tables/het_urban.pdf written in PDF format)

{com}. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/lemartin/Dropbox/Active_Papers/Conjoint_Corruption/Replication files/Martin_Replication_Log.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}17 Feb 2019, 12:28:43
{txt}{.-}
{smcl}
{txt}{sf}{ul off}